chronic absenteeism at one arkansas high school

University of Arkansas, Fayetteville University of Arkansas, Fayetteville

ScholarWorks@UARK ScholarWorks@UARK

Theses and Dissertations

5-2021

Chronic Absenteeism at One Arkansas High School Chronic Absenteeism at One Arkansas High School

Michelle Miller University of Arkansas, Fayetteville

Follow this and additional works at: https://scholarworks.uark.edu/etd

Part of the Accessibility Commons, Educational Assessment, Evaluation, and Research Commons,

Educational Leadership Commons, Educational Sociology Commons, Education Policy Commons,

Scholarship of Teaching and Learning Commons, and the Secondary Education Commons

Citation Citation Miller, M. (2021). Chronic Absenteeism at One Arkansas High School. Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/4032

This Dissertation is brought to you for free and open access by ScholarWorks@UARK. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of ScholarWorks@UARK. For more information, please contact [email protected].

https://scholarworks.uark.edu/

https://scholarworks.uark.edu/etd

https://scholarworks.uark.edu/etd?utm_source=scholarworks.uark.edu%2Fetd%2F4032&utm_medium=PDF&utm_campaign=PDFCoverPages

http://network.bepress.com/hgg/discipline/1318?utm_source=scholarworks.uark.edu%2Fetd%2F4032&utm_medium=PDF&utm_campaign=PDFCoverPages







https://scholarworks.uark.edu/etd/4032?utm_source=scholarworks.uark.edu%2Fetd%2F4032&utm_medium=PDF&utm_campaign=PDFCoverPages

mailto:[email protected]

Chronic Absenteeism at One Arkansas High School

A dissertation submitted in partial fulfillment

of the requirements for the degree of

Doctor of Education in Educational Leadership

by

Michelle Miller

Texas A&M University

Bachelor of Science in Interdisciplinary Studies, 1997

East Central University, 2008

Master of Education in Secondary Education, 2007

Arkansas State University

Specialist in Education in Educational Leadership, 2014

May 2021

University of Arkansas

The dissertation is approved for recommendation to the Graduate Council.

____________________________________ John Pijanowski, Ph.D.

Dissertation Director

____________________________________ Kara Lasater, Ed.D.

Committee Member

___________________________________ Kelli Dougan, Ph.D.

Committee Member

Abstract

Chronic absenteeism is a fairly new concept in education. Many schools have only

started tracking chronic absenteeism with the start of Every Student Succeeds Act. The

following research studied chronic absenteeism at an Arkansas High School, which answered the

two research questions in this study. The first research question studied the demographics of the

chronically absent student which included grade level, race/ethnicity, Special Education and

English Language Learner status, and free or reduced lunch status. The second research question

studied the class period of the chronic absence which included the time of day and type of class.

High School X had 40% of free and reduced lunch students who were chronically absent. The

research also found that twelfth grade students accounted for the highest-grade level of being

chronically absent from one or more of their classes, with 37% in 2016-2017 and 36% in 2017-

2018. The Zero-Hour classes accounted for the highest rate of chronically absent students, with

at least 20% or more of the students enrolled in Zero-Hour being chronically absent. The

research found that the number of students chronically absent from one class period was three

times as high as the students chronically absent from all seven periods.

Acknowledgements

I would like to first thank my dissertation committee, Dr. John Pijanowski, Dr. Kara

Lasater, and Dr. Kelli Dougan. I am very grateful to each of you for your time and expertise in

working with me for the last couple of years on this fulfillment of my dissertation.

Thank you to the people that have influenced my life. Jon Brown, Judy Hamrick, and

Kim Raines Gilligan, high school teachers who gave me confidence in myself. My work family,

Cassy Barnhill, thank you for being there to peer review and tell me to keep going! A huge

heavenly thank you to Steve Jacoby – my mentor – you believed in me and gave me the

opportunity to show my leadership.

I would like to thank my parents, Kipp and Sylvia Miller for the support and love you

have given through the years. The two of you are excellent examples of perseverance and

dedication.

Tracie Miller - what a great sister you are – Thank you for being there to talk about

research and how to write, thank you for always asking where I am at on this journey and

helping to push towards the end!

A big thank you goes out to my boys – Sean, Jeff and Kasen, my extended family –

Donna and Daniel Miller, Randall & Tiffany Latham and Tearney Miller and Kevin Morris–

without family support I wouldn’t be finishing this long journey.

The biggest and most deserving thank you goes to my husband, Tim Miller. Without

you, I wouldn’t be at this point. You pushed, you supported, you gave ideas, you were a

sounding board, and you are my rock. I love you and thank you from the bottom of my heart!

Huge PRAISE to God, many prayers went into this writing and this entire process!

Table of Contents

CHAPTER ONE: INTRODUCTION ............................................................................................. 1

Introduction ................................................................................................................................. 1

Problem Statement ...................................................................................................................... 1

Is Directly Observable ............................................................................................................. 4

Is Actionable ............................................................................................................................ 5

Connects to a Broader Strategy of Improvement .................................................................... 6

Is High-Leverage ..................................................................................................................... 6

Research Questions ..................................................................................................................... 7

Overview of Methodology .......................................................................................................... 7

Positionality ................................................................................................................................. 8

Researcher’s Role .................................................................................................................... 8

Assumptions ............................................................................................................................ 9

Definition of Key Terms ........................................................................................................... 10

Organization of the Dissertation ............................................................................................... 11

CHAPTER TWO: LITERATURE REVIEW ............................................................................... 12

Introduction ............................................................................................................................... 12

Absenteeism........................................................................................................................... 12

Time of Day of Absences ...................................................................................................... 14

Reasons for Absenteeism....................................................................................................... 15

Risks of Chronic Absenteeism .............................................................................................. 16

Demographics of Chronic Absenteeism ................................................................................ 18

Benefits for Raising Attendance and Lowering Chronic Absenteeism ................................. 18

School’s Responsibility ......................................................................................................... 19

Interventions for Attendance and Chronic Absenteeism ....................................................... 20

Conceptual Framework ............................................................................................................. 22

Chapter Summary ...................................................................................................................... 26

CHAPTER THREE: INQUIRY METHODS ............................................................................... 28

Introduction ............................................................................................................................... 28

Rationale.................................................................................................................................... 29

Problem Setting ......................................................................................................................... 30

Research Sample and Data Sources .......................................................................................... 33

Data Collection Methods ........................................................................................................... 33

Data Analysis Methods ............................................................................................................. 34

Trustworthiness ......................................................................................................................... 35

Limitations and Delimitations ................................................................................................... 38

Limitations ............................................................................................................................. 38

Delimitations ......................................................................................................................... 38

Summary ................................................................................................................................... 39

CHAPTER FOUR: RESEARCH ANALYSIS AND RESULTS ................................................. 40

Introduction ............................................................................................................................... 40

Quantitative Data Results .......................................................................................................... 41

Demographic Information ......................................................................................................... 42

Class Period and Subject Matter Information ........................................................................... 50

CHAPTER FIVE: ANALYSIS, IMPLICATIONS AND RECOMMENDATIONS ................... 99

Introduction ............................................................................................................................... 99

Research Question One ....................................................................................................... 100

Research Question Two ....................................................................................................... 104

Implications ............................................................................................................................. 110

Demographics ...................................................................................................................... 110

Recommendations ................................................................................................................... 113

References ................................................................................................................................... 117

1

CHAPTER ONE: INTRODUCTION

Introduction

This research provides insight and understanding of chronically absent students and their

common characteristics at High School X. Chronic absenteeism is defined as the student missing

more than 10% of the academic school year due to excused absences, unexcused absences, and

suspensions (Arkansas Department of Education, 2018). For students at High School X, this

would imply missing nine days or more, since students are on a block schedule where a standard

school year contains ninety days to be considered chronically absent.

Problem Statement

In High School X, 1,142 students were chronically absent in one or more classes during

the 2018-2019 school year. Chronic absences are a situation that plagues a majority of schools

in the United States (U.S.), “…each year an estimated 5 million to 7.5 million U.S. students miss

nearly a month of school” (Ginsburg, Jordan, & Chang, 2014, p. 2). Chronic absences are a

situation that leads to lack of educational development in the student, which may lead to

dropping out of school and being unsuccessful in life (Garcia & Weiss, 2018; Ginsburg et al.,

2014; London, Sanchez, & Castrechini, 2016). “Chronic absenteeism can wreak havoc long

before it is discovered. That havoc may have undermined school reform efforts of the past

quarter century and negated the positive impact of future efforts” (Balfanz & Byrnes, 2012, p. 4).

This research provides insight and an understanding of student’s characteristics who are

chronically absent at High School X. Low attendance rates are shown to be a determining factor

in the success of students. Students who are chronically absent have several factors that can

deter their success in school and future success after school. Students from poverty/low

socioeconomic situations are at a disadvantage because of the struggles poverty creates, which

2

leads to higher absentee rates (Epstein & Sheldon, 2002; Van Eck, Johnson, Bettencourt, &

Johnson, 2017). Situations of poverty/low socioeconomic students includes a “…lack of

adequate transportation, unsafe conditions, lack of medical services” (Garcia & Weiss, 2018, p.

5), which all contribute to this group having a higher absentee rate than their higher socio-

economic peers.

Poor and somewhat poor students (those who qualified for free lunch or for reduced-price

lunch) and students with disabilities (those who had individualized education programs or

IEPs) were much more likely than their more affluent or non-IEP peers to miss a lot of

school. (Garcia & Weiss, 2018, p. 3)

There are many reasons that attribute to this lower attendance rate including higher medical

issues and sickness, lack of relationships with staff members on campus, and lower achievement

from students (London at al., 2016). High School X is concerned with attendance rates and the

number of students losing credit due to eight or more absences in a class, which was the

attendance policy during the 2016-2017 school year. In spring 2017, there were over 650

students who had eight or more absences in one or more of their classes. These students were in

danger of not receiving credit for these classes, which would impact their ability to meet all

graduation requirements and graduate from high school. One of the major contributing factors

on why students do not graduate is a failure to attend class (Gottfried & Hutt, 2019; Ahmad &

Miller, 2015). A failure to attend class, disconnection with school, and disengagement from the

students are all consequences of chronic absenteeism. This disconnection and disengagement are

demonstrated when students are not involved and do not earn passing grades in class. Students

who are not coming to school leads to low grades and eventually dropping out of school before

graduation (London et al., 2016; United States Department of Justice, 2015). These dropouts are

more likely to become low income wage earners and end up in the judicial system (Ahmad &

Miller, 2015; Garry, 1996).

3

With a population of 2,700 students at High School X, the 650 students represented

roughly 25% of the student body population. During the 2016-2017 and 2017-2018 school

years, the attendance policy was stated in a way that students would lose credit when they

exceeded the number of absences allowed for each class. During the 2015-2016 school year, the

number of allowed absences before losing credit was twelve. During the 2016-2017 and 2017-

2018 school years, the number of allowed absences was dropped to eight. In 2018-2019 school

year, the District school board changed the attendance policy to allow six excused absences and

five unexcused absences before the possibility of losing course credit. Attendance policies are

set by individual school boards and can vary greatly across school districts and states. The total

number of absences allowed by school attendance policies during the researched school years

does not represent the threshold for this research study. This research focused on students who

met the definition of chronic absenteeism, which meant missing 10% of their school days, and

researching similarities in those students. By researching the commonalities of chronically

absent students, potential changes in policy and procedures could be discussed to target and

address the student commonalities.

Focus on Systemic Issues

As aforementioned, chronic absenteeism is a problem, especially for secondary schools.

According to the United States Department of Education (2016), nearly 20% of high school

students are considered chronically absent.

Most school districts and states don’t look at all the right data to improve school

attendance. They track how many students show up every day and how many are

skipping school without an excuse but not how many are missing so many days in

excused and unexcused absence that they are headed off track academically. (Chang,

Russell-Tucker, & Sullivan, 2016, p. 26)

4

“A school with a 90% ADA (Average Daily Absence) rate can have 25% or more of its student

chronically absent in a given year…if the problem remains hidden in plain sight, students and

schools suffer” (George W. Bush Institute, 2018, p. 3). Absenteeism can contribute to students

not being engaged in school and then deciding to drop out (Ahmad & Miller, 2015). “To prevent

and correct serious attendance problems, schools need to change the way they are structured,

improve the quality of courses, and intensify interpersonal relationships between student and

teachers” (Epstein & Sheldon, 2002, p. 309). Students who are high school dropouts are more

likely to live in poverty, due to the lack of education and opportunities for job advancement.

“High school dropout, which chronically absent students are more likely to experience, has been

linked to poor outcomes later in life, from poverty and diminished health, to involvement in

criminal justice system” (United States Department of Education, 2016, p. 8).

Is Directly Observable

The research data for chronic absenteeism speaks for itself. Nearly 20% of high school

students are chronically absent (United States Department of Education, 2016). Nationwide, this

means more than 3 million students are chronically absent each year. Unfortunately, High

School X is no exception to this grim statistic. During the 2016-2017 school year, 773 students

were chronically absent in one or more classes, which was equivalent to 28.7% of the student

body. During the 2017-2018 school year, 916 students were chronically absent in one or more

classes, which was equivalent to 35.6% of the student body. During the 2018-2019 school year

1,142 students where chronically absent in one or more classes, which represented 44.2% of the

student body. Within these percentages, individual demographic groups may have higher

percentages of chronic absenteeism as shown by national averages. For example, African-

Americans (23%), Multiracial (21%), and Latinos (21%) accounted for the high percentages of

5

chronic absenteeism by demographic group (United States Department of Education, 2016). The

breakdown of demographics at High School X is as follows: English Language Learner (ELL)

(7%), Low-Income (31%), Students with Individualized Education Plan (IEP) (13%), African-

American (10%), Hispanic (13%), and White (67%). The percentages of chronically absent

students for High School X were researched and compared to the national averages in this

research study.

Is Actionable

The Hamilton Project stated, “What gets measured gets done” (Bauer, Liu,

Schanzenbach, & Shambaugh, 2018, p. 6). This statement refers to school improvement and

how accountability measures matter as schools focus on and strive to make the necessary

improvements within their systems. “If chronic absenteeism were included in the accountability

mix with student achievement and graduation rates, we would expect schools to improve

attendance measurement and work to reduce absences” (Bauer et al., 2018, p. 6). Both of these

statements reflect the need to have accountability measures on chronic absenteeism in place at

school. The importance of identifying students who are chronically absent and reviewing their

absenteeism commonalities will allow schools to have the necessary information to make

decisions and policies. Every Student Succeeds Act (ESSA) for Arkansas has included a school

rating category for chronic absenteeism.

Despite being pervasive, though overlooked, chronic absenteeism is raising flags in some

schools and communities. This awareness is leading to attendance campaigns that are so

vigorous and comprehensive they pay off quickly. Examples of progress nationally and

at state, district, and school levels give hope to the challenge of chronic absenteeism,

besides being models for others. (Balfanz & Byrnes, 2012, p. 7)

6

Connects to a Broader Strategy of Improvement

In 2015, the Obama Administration created an initiative called My Brother’s Keeper-

Success Mentor Initiative (MBK), which established a partnership between chronically absent

students and mentors from the school system to “…improve their school attendance and

achievement” (United States Department of Education, 2016, p. 7). During the 2015 White

House administration, the Every Student Succeeds Act (ESSA) gave each state the opportunity to

of design “…their own accountability system” (Bauer et al., 2018, p. 5). Within this

accountability system, each state must have at least one measure of school quality. Chronic

absenteeism was one factor that 36 states chose to incorporate into their accountability plan

(Bauer et al., 2018). “The newly enacted ESSA law required the reporting of chronic

absenteeism at school and district levels, and it allows the use of federal funds for preventative

measures and training to reduce chronic absenteeism” (Lara, Noble, Pelika, Coons, & National,

2018, p. 1). The ESSA for Arkansas includes chronic absenteeism as one of the items for

accountability in schools. In order to improve chronic absenteeism, an understanding of the

factors contributing to these absences needs to be identified. Early intervention in high school is

needed to monitor these students, “(A) chronically absent student in grade 9 has a .68 probability

of being chronically absent in grade 10” (Gottfried & Hutt, 2019b, p. 21).

Is High-Leverage

The issue of absenteeism is high-leverage because students who are chronically absent

from school miss opportunities for academics, as well as extra-curricular activities. In addition,

students who are chronically absent have lower scores on standardized assessments. For

example, eighth grade chronically absent “…students scored an average 18 points lower on math

assessment” (Ginsburg et al., 2014, p. 3). When students are chronically absent, there are a

7

multitude of effects that can occur throughout a student’s academic career including a decline in

various personality constructs such as grit and perseverance, increased drop-out rates in high

school, and more difficulty in completing college (Ginsburg et al., 2014). Balfanz and Byrnes

(2012) posed if students from high-poverty families attended school every day with no other

changes, they would experience “…increased rates of academic achievement, high school

completion, post-secondary education attainment and economic productivity” (Ahmad & Miller,

2015, p. 6). One category of chronic absenteeism is truancy, which is also high-leverage because

“50 percent of all truants ended up with a criminal charge by the time they turned 18 years old …

compared to only 12 percent of nontruant students” (Ahmad & Miller, 2015, p. 13).

Research Questions

1. What correlation, if any, does demographic information have with students’ chronic

absenteeism at High School X?

2. What are the correlations among students’ chronic absenteeism and the class period

of the absence?

Overview of Methodology

The research method used for this study was a non-experimental, correlational

quantitative design. The information gained from this research study was best answered by

using a quantitative analysis. The researcher accessed the Arkansas Public School Computer

Network (APSCN) and Cognos systems for the quantitative data. This system allowed the

researcher to access archival attendance record data for the 2016-2017, 2017-2018, and 2018-

2019 school years. The use of Cognos, a report generator within APSCN identified students who

were chronically absent during each school year. This system also allowed for a review of

student information such as demographics to determine if there were similarities in the students

8

who were chronically absent. The similarities found within the data helped determine the next

steps in changing the level of chronic absenteeism at High School X. These student similarities

could lead in providing changes to policy and procedures that are used at High School X. The

demographic information obtained through APSCN and COGNOS contained grade level,

race/ethnicity, lunch status, and English Language Learner (ELL) or Special Education (SPED)

status. The chronically absent student information allowed the researcher a thorough review into

the class periods with the most absences to determine if there were similarities within the data.

This information included the time of day of the absence, where the class period fell in the

schedule, and the subject and academic department of the course.

Positionality

Positionality is the influence of the researchers own ideas and experiences regarding the

research study. Positionality also influenced the way the researcher thought about the research,

and the attendance rates and policies at the school district where the researcher is employed.

Researcher’s Role

The researcher’s current role at High School X is an assistant principal and has been for

the past five years. Before accepting her current position, the researcher was a teacher of

mathematics at High School X. The researcher has been impacted by chronically absent students

at X Public Schools as a teacher and administrator. In her first three years as an administrator,

she was responsible for the implementation of the district attendance policy, through

enforcement of the denial of credit policy. In this role, the researcher determined if the students

met, or did not meet the district attendance policy and if students did not meet the attendance

policy, the researcher followed through by denying their credit for the course based on the

attendance policy. Recently, this attendance policy has changed if the student has too many

9

absences. The policy now allows the principal to determine if the number of absences has

reached the point where the school district denies credit for a course. Since the attendance policy

was the researcher’s responsibility for the last several years, she understood the impact of that

policy as a teacher and now as an administrator. Currently, the researcher is trying to determine

what impact she, or the school can do to help students who are chronically absent and improve

their attendance. The answers to the research questions could provide similarities of students

who were chronically absent; therefore, it will provide a starting point to begin making changes

regarding chronic absenteeism at High School X.

The researcher is also a member of the community and has children attending schools

within the district. She has a vested interest in determining what impact attendance policies have

on these chronically absent students. The researcher has seen firsthand the impact grades and

behaviors has on students when they do not attend class(es). She has seen students drop-out and

leave school because they felt like they were too far behind since they had not attended class and

had a high absentee rate. She believes this research study will help provide an in-depth

understanding of the factors impacting chronically absent students.

Assumptions

The researcher’s role and background may lead to several biases on the topic of high

school student attendance. The researcher was brought up in a middle class, Caucasian family

where education was highly valued. Her mother was a teacher and later a principal. When her

father retired from the military, he became a school guidance counselor at an alternative school.

The value of education was always at the forefront of the researcher’s upbringing. With this

value in education, there was an understanding that children attended school every day unless

there was an illness, or on some sort of school sponsored trip. There was never a question in

10

whether or not the researcher was going to attend class. These expectations were presented from

the researcher’s parents, and she met their expectations. The researcher also believed that

everyone had the same thoughts about attending classes and school. She surrounded herself with

peers of a similar mindset, and continues to do so today. The researcher is surrounded by other

parents who value their children’s education and success.

As an administrator, the researcher’s bias also included thoughts of why students come to

school, but not attend class(es). The researcher’s assumptions to these questions include students

being more motivated by their peers and their social activities. If a student has a social group

where attendance is not a priority; therefore, that group of peers will not attend classes together.

Another assumption is the relationship students have with their teachers. If a student does not

feel connected to the teacher, the researcher believes they will not attend or feel they have a

reason to attend the class.

Definition of Key Terms

Chronic Absenteeism (CA) - This occurs when a student is absent for more than 10%

of the school year. For High School X, this would be approximately nine days due to

the block schedule, which students attend for 90 days in each class during the school

year.

Attendance Rates - The percentage of time a student is in school.

Excused Absence - An absence in which a parent/guardian has provided

documentation, or has notified the school of the absence. Documentation examples

include a parent note, a doctor’s note, or documentation from a court.

Truancy - This is when a student skips a class.

11

Unexcused Absence - An absence in which the student has no documentation.

Documentation examples would include a parent note, a doctor’s note, or

documentation from a court.

APSCN – This is the Arkansas Public School Computer Network database used by

Arkansas Department of Education. The system includes all student and teacher data

in the Arkansas public school system.

COGNOS – A report generator within APSCN.

Organization of the Dissertation

Chapter Two provides a review of the literature surrounding the concept of chronic

absenteeism. This chapter also provides information on the Social Learning Theory and how it

relates to the topic of chronic absenteeism.

Chapter Three offers a presentation and discussion of the research study methodology

used to acquire the data and the data analysis to help answer the two research questions posed in

this study.

Chapter Four presents the data obtained concerning chronic absenteeism for the 2016-

2017, 2017-2018, and 2018-2019 school years at High School X. This chapter is divided into

answering both research questions in this study.

Chapter Five includes the analysis, implications, and recommendations for future

research and practice, while analyzing the link between the national trends and the data at High

School X.

12

CHAPTER TWO: LITERATURE REVIEW

Introduction

This research provides insight and understanding of students and their common

characteristics as determined by a review of literature. This chapter focused on previous

research including absenteeism, chronic absenteeism, demographics of students who were

chronically absent, time of day students were absent, and interventions. The previously

published research was used to help determine the perceived factors in chronic absenteeism and

ways to improve attendance. The databases used to research these topics were ERIC database,

the University of Arkansas library, and Google Scholar. In order to locate this research, the

researcher used the following search terms such as “partial day absences,” “chronic

absenteeism,” “secondary school attendance,” “secondary school truancy,” “attendance policies

at secondary schools,” “Social Learning Theory,” “Socialization,” and “time of day absences.”

Table 2.1 presents the types of research materials included in the review of literature.

Table 2.1

Literature Review of Source Information

Type of Source Number Reviewed

Peer Reviewed Articles 35

Government Reports 5

Scholarly Websites 3

Scholarly Books 7

Absenteeism

Chronic absenteeism is defined as “…missing 10% or more of school days in a school

year for any reason, excused or unexcused” (United States Department of Education, 2016, p. 1).

The actual number of school days can vary by state anywhere from 180 to 220 days, which

means being chronically absent can also fluctuate by state (Garcia & Weiss, 2018). By this

definition, chronic absenteeism is defined as a student who misses nine school days within each

13

class period due to the block schedule at High School X. With the school year being over a ten-

month period, a student would only need to miss one or two days per month to be considered

chronically absent. Within this study, this was the definition of “chronic absenteeism” used to

describe students with excessive absences. Most of the previous research conducted was based

on attendance rates, such as daily attendance rates. Before ESSA was put in place, “Elementary

schools often track average daily attendance or unexcused absences (truancy), but few monitor

the combination of excused and unexcused absences for individual students” (Chang & Romero,

2008, p. 3). This is another example of why research needs to focus on the individual student

who is considered chronically absent, not only the attendance rate for the school as a whole.

“With this relatively small literature about students who fall into this recently developed

definition of chronically absent, we know little about how this designation affects their current

and future academic trajectories, particularly at the middle and high school levels” (London et

al., 2016, p .7). Truancy and absenteeism are closely related in definition. Absenteeism is both

excused and unexcused absences, while truancy is only unexcused absences (Ahmad & Miller,

2015). In most states, truancy is considered a status offense, “…meaning it is an offense that

would not be considered unlawful if committed by an adult” (Ahmad & Miller, 2015, p. 4).

There are multiple theories as to why there is high absenteeism for some students.

According to the Indiana Department of Education (Lochmiller, 2013), these reasons include

physical health, mental health, student perceptions of the school, parent and family predictors,

family socioeconomic status, composition and family involvement, school culture, nature of the

academic program, and condition of the school facility (Lochmiller, 2013).

14

Time of Day of Absences

According to Whitney and Liu (2017), “The underestimation of school absence is

problematic, especially if part-day absence has similar detrimental effects on student learning

and development to full-day absence” (p. 2). Historically, absences are only counted by full day

absences. “Although scholars and practitioners agree that absence in secondary school is a

problem, the empirical literature on the prevalence and potential reasons for absence is relatively

weak, largely due to the lack of detailed class-level attendance data” (Whitney & Lui, 2017, p.

2). The lack of research completed on the impact of a partial day or per period absence is a

cause for concern. “(P)art day absenteeism is responsible for as many classes missed as full-day

absenteeism, raising chronic absenteeism from 9% to 24% of secondary students” (Whitney &

Liu, 2017, p. 1). At the high school level, a credit is awarded for each individual class towards

graduation. Since an absence in one class, could be as detrimental as absences in all classes, and

understanding of individual absences is important.

Specifically, we find that having a class in first period increases absences in that subject

by four to seven days over the year and that it decreases class performance in that subject

by 0.11 to 0.17 grade points on a four-point grading scale. (Cortes, Bricker, & Rohlfs,

2012, p. 2)

Many absences at the high school level are due to partial day absences and not full day absences.

Slightly more than half (55%) of full day absences are unexcused. However, 92% of

part-day absences are unexcused rather than excused. In sum, when students are absent

from middle or high school on a given day, they are most often accruing unexcused

absences from some but not all of their classes. (Whitney & Liu, 2017, p. 5)

The previous statement emphasized the concept of the importance of studying partial day

absences, whether those absences are excused or unexcused, they would be included in chronic

absentee totals. A high school student may have four to eight teachers in a single day. These

teachers may be unaware of a student’s attendance in a previous class earlier in the day, and

15

simply mark a student absent when they are not in their class. If a high school student leaves

campus, they usually do so on their own.

Once students enter high school, they experience much more freedom. They change

classes and go to lunch and the library by themselves, with no adult supervision. They

may see each teacher for less than an hour a day, making it less likely they will have an

adult looking out for them throughout the day. As a result, it becomes easier for student

to skip classes. (Allensworth, Gwynne, Moore, & Torre, 2014, p. 23)

Each absence a high school student accumulates can contribute to the possibility of not receiving

a credit in that class. There is a need for research to be conducted focused on partial day

absences. The research may suggest that a partial day absence for a high school student can be

as detrimental towards graduation as a full day absence.

Does the type of class impact a student’s attendance in certain classes? Do students miss

or attend classes required for graduation more than they attend classes that receive no credit? Do

students attend core classes such as Mathematics, Science, English, and Social Studies more than

they attend their elective classes? Each of these questions must be answered to better understand

high school student absences. According to Whitney and Lui (2017), “Students are only slightly

less likely to have an unexcused class absence from a core class than from a noncore class” (p.

14). Cortes et al. (2012) found “…having a class first period of the day increases absences in

that subject by four to seven days over the year” (p. 2).

Reasons for Absenteeism

Previous research provided a multitude of reasons why a student is absent from class.

Balfanz and Byrnes (2012) condensed the reasons into three broad categories including students

who cannot attend, students who will not attend, and students who do not attend. “Students who

cannot attend due to illness, family responsibilities, housing instability, the need to work, or

involvement with the juvenile justice system” (Balfanz & Byrnes, 2012, p. 7). “Students who

16

will not attend school to avoid bullying, unsafe conditions, harassment, and embarrassment”

(Balfanz & Byrnes, 2012, p. 7). “Students who do not attend school because they, or their

parents, do not see value in being there, they have something else they would rather do, or

nothing stops them from skipping school” (Balfanz & Byrnes, 2012, p. 7).

Within the “cannot attend” category, some of these reasons are tied to family concerns,

such as single-parent households (Jones, Finnegan, & Harris, 2002), and the inability for a parent

to provide consistent and effective discipline (Corville-Smith, Ryan, Adams, & Dalicandro,

1998). “Student health plays a large role in chronic absenteeism” (Bauer et al., 2018, p. 19).

Poverty is another factor that contributes to chronic absenteeism. “Poor students are

substantially more likely than non-poor students to be chronically absent” (Bauer et al., 2018, p.

19).

Another reason for absenteeism is tied directly to the student, which connects with the

“do not attend” category. There were times where the student decided to not go to school and

could possibly be when social time with their friends was more important than attending class.

“(P)arents are unaware of or have not approved the student’s absence, implying a measure of

student volition in the absence decision” (London et al., 2016, p.4).

In the category of the students who “will not attend” could be due to factors at the school.

One school factor contributing to student absenteeism was not engaging in a positive relationship

with staff (Corville-Smith et al., 1998).

Risks of Chronic Absenteeism

According to the Arkansas Department of Education (2018), “Chronic absence is missing

so much school for any reason that a student is academically at risk. It means missing 10% or

more of the school year for any reason – excused, unexcused, and suspended” (p.1). A student

17

who has chronic absenteeism throughout their school years were more likely to drop out of

school, have lower levels of social engagement, and less likely to graduate high school, or attend

college (Ginsberg et al., 2014). With truancy being one of the categories of chronic absenteeism,

many times “…truants have a higher high school drop-out rate because, in many cases, dropping

out is easier than catching up” (Ahmad & Miller, 2015, p. 9).

Students from poverty were more likely to be chronically absent from school and miss

the positive impact an education can provide in life. “(C)hronically truant students experience

employment-related difficulties such as lower-status occupations, less stable career patterns,

higher unemployment rates, and low earnings as adults” (Ahmad & Miller, 2015, p. 8).

Students who were chronically absent were more likely to be involved with the criminal

justice system. Compulsory education laws are in place by all states. “Compulsory school

attendance and truancy policies in the United States have focused on parental responsibility, age

of compulsory school attendance, and punishment for various forms of chronic absences”

(Reyes, 2020, p. 1). “Criminal records review … revealed that … 26 percent of truant students

had already come into contact with the criminal justice system, prior to receiving a truancy

petition” (Ahmad & Miller, 2015, p. 13). Furthermore, research found students who were truant

early in their academic career were more likely to commit violent crimes, and more likely to be

incarcerated (Jones, Lovrich, & Lovrich, 2011). The involvement with the criminal justice

system may not always be in the criminal side of chronic absenteeism, but also students who

were victims of violence. “92 percent of the victims were chronically truant” (Baltimore City

Health Department, 2009, p. 4). “Truancy has been identified as an early warning sign that a

student is headed for educational failure via suspension, expulsion, dropping out, or delinquent

activity” (Bridge, Curtis, & Oakley, 2013, p. 2).

18

Demographics of Chronic Absenteeism

By observing the national trends for chronic absenteeism and relating them to the

demographic data at High School X, this information will provide insight into whether High

School X students are similar to the national trends, or if this school district is an outlier. If the

data shows outliers, the next step would lead to discussions at High School X on why the student

population is different than the national trends, and what can be done to make a difference in

these student’s chronic absenteeism. What is different about the system at High School X that

does not lend itself to the nationwide data? According to the 2013-2014 Civil Rights Data

Collection, 14% of all students were chronically absent, which meant they missed 15 or more

days during the school year. This rate was higher at the high school level as 19% of students

were chronically absent. Again, this data only focused on full day absences and not per class

absence, which could be argued as being as detrimental to the chronic absenteeism research.

Within the numbers and demographics of chronically absent, Black (23%), Latino (21%), and a

“(h)igh school student with disabilities served by IDEA are 1.4 times as likely to be chronically

absent as high school students without disabilities” (United States department of Education,

2016, p. 7). “Among students missing more than 10 days of school, the share of free-lunch

eligible students was more than twice as large as the share of the non-FRPL-eligible students”

(Garcia & Weiss, 2018, p. 4).

Benefits for Raising Attendance and Lowering Chronic Absenteeism

The benefits for raising attendance requirements are advantageous for both the student

and the school/school district. “When students reduce absences, they can make academic gains”

(Ginsburg et al., 2014, p. 6). According to Ginsberg et al. (2014), when schools focused on

attendance, graduation rates rose. They further stated, “Children who arrived with the weakest

19

skills and attended regularly saw outsized gains in achievement” (p. 6). In another study which

focused on attendance and improvement of attendance, chronic absenteeism dropped 7%, while

scores on a reading assessment improved by 9% (Chang et al., 2016). A focus on attendance not

only improves the educational experience for students who are chronically absent, but also for

the students who attend regularly. “The educational experiences of children who attend school

regularly can be diminished when teachers must divert their attention to meet the learning and

social needs of children who miss substantial amounts of school” (Chang & Romero, 2008, p. 3).

From the school district perspective, the benefits of improving attendance for the school

district can be monetary in nature. “In a three-year period, California school districts have lost a

total of $4.5 billion due to absenteeism” (Gottfried & Hutt, 2019a, p. 3). Epstein and Sheldon

(2002) reiterated this information “…school funding is often at least partially dependent on the

number of students who regularly attend” (p. 308). Both of these studies proved the importance

of increasing the attendance rate of students.

School’s Responsibility

Part of the responsibility for chronic absenteeism lies within the school system and how

they handle these situations with students. It is necessary to state that suspension is listed as a

reason for missing school. At High School X, administrators are reviewing the number of

suspensions and exploring alternate consequences that do not involve the student missing school.

“The counterintuitive response of suspending a truant student further removes the student from

the learning environment, which could reinforce the undesirable behavior” (Anderson, Egalite, &

Mills, 2019, p. 151). According to the data from the 2016-2017, 2017-2018, and 2018-2019

school years, there are a number of suspensions over ten days. When those days are added to the

total number of absences for each student; the student would be considered chronically absent by

20

the definition of chronic absenteeism. As a school system, the administrators review ways to

reinforce positive behavior and provide consequences that do not involve being out of school,

until it is absolutely necessary. “When students are repeatedly absent from school, they miss

important learning and developmental opportunities which can potentially have negative

consequences on their future outcomes” (London et al., 2016, p. 3). Absences because of school

suspensions can lead to a student being chronically absent. This issue must be a focus for High

School X and figure out how to keep the student in school rather than suspending them. “Life

conditions can often dictate the priorities in a youth’s life, where supplementing familial income

may become more important than attending school on a regular basis” (Birioukov, 2016, p. 341).

By providing opportunities for students to receive credit towards graduation while having a job,

it may provide them opportunities to keep their job and family support, but still be able to attend

school.

Interventions for Attendance and Chronic Absenteeism

After reviewing the literature, there were several interventions that were to help raise

attendance levels across the country. Chang and Romero (2008) provided the following diagram

to demonstrate some of these interventions in Figure 2.1.

21

Figure 2.1. Interventions for Attendance. (Chang & Romero, 2008, p.7)

“Taking a comprehensive approach to family, school, and community partnerships has also been

shown to improve attendance and reduce the rates of chronic absence in schools” (Epstein &

Sheldon, 2002, p. 315). London et al. (2016) outlined three specific policy interventions that

must be in place to ensure chronic absenteeism improves among students. The first intervention

was to ensure a state has a definition for chronic absenteeism. The state of Arkansas has

completed this policy. The second intervention was for schools and districts to track attendance

for each individual student, “…simple data collection and analysis tools are developed, which

enable teachers and administrators to identify when, where, and which students misbehave or do

not attend” (Balfanz, Herzog, & MacIver, 2007, p. 232). The third intervention was “…to enact

policies that describe the intervention process, not only for chronically absent students, but also

for their parents or guardians who may know about, and even condone, students’ absences”

22

(London et al., 2016, p. 22). The Juvenile Justice and Delinquency Office discussed the ability

to provide “…programs ranging from mentoring programs to parent training to direct provision

of services” (Ahmad & Miller, 2015, p. 1) as another avenue of intervention for students and

families. Another proven intervention to improve student attendance was determining the level

of engagement students had in an individual teacher’s classroom. “Having more engaging

teachers increases not only attendance in the year in which the student has the teacher but also

improves students’ chances of completing high school” (Liu & Loeb, 2016, p. 6). Each of these

interventions different schools have used provided ideas and resources to be included in the

prevention of chronic absenteeism.

Conceptual Framework

The review of literature provided an in-depth look at the reasons behind chronic

absenteeism, specifically in relation to high school students. The review of literature provided an

understanding in the need for further investigation into students who are only missing parts of a

school day, such as a class period or two, which may be as detrimental as missing a full class day

(Whitney & Liu, 2017). The majority of data collected has studied the chronic absenteeism of

students nationwide where a chronic absence is a full day absence (Whitney & Liu, 2017). The

review of literature also examined the benefits of increasing attendance and interventions that

may be helpful in decreasing chronic absenteeism (Chang & Romero, 2008). By reviewing each

of these areas, the previous research provided some guidance in making future decisions at High

School X.

A conceptual framework allows you to…explore research topics…explore existing

research questions…using different theoretical, epistemological, and methodological

frames and approaches. Conceptual frameworks match your research questions with

those choices, an in turn align your analytic tools and methods with your questions.

(Ravitch & Riggan, 2017, p. 17)

23

The theory behind understanding chronic absenteeism and ways to improve attendance

can be associated with Social Learning Theory and Socialization. According to many theorists

on socialization, such as Piaget, Kohlberg, Lundberg and Mead, who believe socialization

influence cognitive development and “Socialization consists of the complex processes of

interaction through which the individual learns the habits, beliefs, skills and standards of

judgment that are necessary for his effective participation in social groups and communities”

(Shah, 2017, p. 1). The issues of chronic absenteeism can be closely tied with socialization

theory. Many values, habits, and attitudes are initially taught and promoted by a student’s

family. The family aspect of chronic absenteeism is very important (Hanover, 2016).

Research showed that parents who do not realize the impact of missing two or three days a

month can have on a student being classified as chronically absent is very concerning (Chang

& Romero, 2008).

The theory of socialization is influenced by several theorists with each having their

own version of the theory. George Hubert Mead believed children learn through interaction

with significant others such as parents or siblings, and then through generalized others

including peers, or society itself (Cronk, 1995). Lawrence Kohlberg and Carol Gilligan were

also socialization theorists who focused on the development of boys and girls. Each focused

on the role of society and the formation of development in boys and girls (Kohlberg, 1969;

Gilligan, 1982).

Socialization theory continues through high school age where students begin to

express their own beliefs and start to be influenced by the beliefs of their peers. High school

age students tend to miss school with a social group (Brown, Mounts, Lamborn, & Steinberg,

1993). Socialization theory at the high school age moves from family values to the building

24

of their own values, habits, and attitudes, which are influenced by their peers. Socialization is

the influence of society on an individual, and for a high school student, their society is

primarily going to be their peer group.

Socialization at the high school level is also influenced by school district policies.

Socialization is the understanding of society attitudes. The society attitudes at the high school

level can be demonstrated by the attendance expectations of a school district. The current

attendance policy at X School district allows for a student to miss five days with an excused

absence and six days with an unexcused absence. These absences would represent the society

attitudes concerning absenteeism for the school district. This attendance policy should help

mold the expectations for students to attend high school in this school district.

The second theory being used to guide the understanding of students who are

chronically absent at High School X is Social Learning Theory. As explained by Albert

Bandera, Social Learning Theory is tied closely to Socialization, but with an added

component of reinforcement.

Social learning theory combines cognitive learning theory, which posits that learning is

influenced by psychological factors, and behavioral learning theory, which assumes that

learning is based on responses to environmental stimuli. Psychologist Albert Bandura

integrated these two theories in an approach called social learning theory and identified

four requirements for learning—observation (environmental), retention (cognitive),

reproduction (cognitive), and motivation (both). (Theory, 2017, p. 1)

An, extrinsic reward is graduation and students are more likely to graduate because they

achieved all required graduation credits. The idea of creating policies that provide

reinforcement such as consequences or punishment including loss of credit, and loss of

privilege would likely represent a positive punishment in the attendance of students. Another

positive punishment occurs when the court system becomes involved in adjudicating

absenteeism. High School X utilizes the Family in Need of Services (FINS), specifically in

https://www.psychologytoday.com/us/basics/motivation

25

cases where students are chronically absent. A FINS case implies the school has submitted

the name of a student to the court system who needs to be investigated, and possibly impose

consequences on the student and/or parent for the lack of attendance at school.

Social Learning Theory allows for the idea that students can reinforce their behavior

both positively and negatively among their social group. “What are they doing when they are

not in school? “Hanging out with friends” is the most common activity (65 percent) when

skipping school” (Garin, 2012, p. 2).

Traditional theories of learning generally depict behavior as the product of directly

experienced response consequences. In actuality, virtually all learning phenomena

resulting from direct experiences can occur on a vicarious basis through observation of

other people’s behavior and its consequences for them. (Bandura, 1971, p. 2)

Bandura led the researcher to believe, if a student is a member of a social group that are

chronically absent, then the student’s own behavior would potentially emulate that chronically

absent behavior as demonstrated in Figure 2.2.

26

Figure 2.2. Conceptual Framework in Visual Form.

Chapter Summary

This chapter provided a detailed examination of the previously published literature and

the conceptual framework associated with the concept of chronic absenteeism. The literature

review provided an in-depth discussion on absenteeism, time of day of absences, reasons for

absenteeism, risks of chronic absenteeism, demographics of absenteeism, benefits for raising

attendance, and interventions for attendance. Each of these categories provided published

literature focused on the importance and the inclusion of this topic at High School X. The

conceptual framework focused on theories that were connected to absenteeism and the mindset

behind understanding students thinking and what influences their decisions. By using

Reasons for

absenteeism

Time of day of

absence

Risks for chronic

absenteeism

Benefits for Raising

Attendance

Demographics

of chronic

absenteeism

Interventions for

Attendance

Chronic Absenteeism at

High School X

Ways to

improve

attendance

Informs

Informs

Informs

27

Socialization and Social Learning Theory to help understand the complexities of chronic

absenteeism, it provides a strong frame of reference for this research study.

28

CHAPTER THREE: INQUIRY METHODS

Introduction

This research provided insight and understanding of chronically absent students and their

common characteristics at High School X. Chronic absenteeism is a concern for schools across

the country. The methodology used for this study was a non-experimental, correlational

quantitative study of High School X. The Arkansas Department of Education, Arkansas Public

School Computer Network (APSCN) provided the archival data for the quantitative analysis.

This data allowed the researcher to analyze the characteristics of students with chronic

absenteeism. The data also provided the opportunity to analyze the classes students were

chronically absent from during the day. By knowing the class periods, it was important in

determining the patterns for absenteeism. In the state of Arkansas, chronic absenteeism is

defined as a student missing more than 10% of the academic school year due to excused

absences, unexcused absences, and school suspension (ADE, 2018). Student chronic absences

plague a majority of schools in the United States, “…poor attendance is a national challenge”

(Ginsburg et al., 2014, p. 3). Chronic absenteeism leads to a lack of student educational

development, and may lead to a student dropping out of school and being unsuccessful in life

(Ginsburg et al., 2014). At High School X, chronic absenteeism is a situation that plagues some

students, and may lead to them being unsuccessful in completing the credits necessary to

graduate high school. In this study, the research approach used was a quantitative analysis. The

researcher analyzed the data for High School X to answer the following research questions:



29

2. What are the correlations among students’ chronic absenteeism and the class period

of the absence?

Rationale

The research method used for this study was a non-experimental, correlational

quantitative study of the data. “The purpose of correlational studies is to discover, and then

possibly measure, relationships between two or more variables” (Mertler, 2019, p. 101). Mertler

(2019) also stated:

Correlational research in education seeks out traits, abilities, or conditions that covary,

or co-relate, with each other. Understanding the nature and strength of the relationship

between two or more variables can help us:

comprehend and describe certain related events, conditions, and behaviors

(correlational studies with this goal are typically referred to as explanatory

correlational studies);

predict future conditions or behaviors in one variable from what we presently know of

another variable (these studies are generally referred to as predictive correlational

studies); and

sometimes obtain strong suspicions that one variable may be “causing” the other. (p.

101)

The research questions were answered by a quantitative data analysis. The quantitative data was

important to this study in determining who the chronically absent students were at High School

X. The quantitative research data also included analyzing the types of classes, the time of the

classes, and the demographics of the students. The quantitative data allowed for a correlational

analysis to determine if a relationship existed between the demographic information of a student

and the chronic absenteeism of a student. The quantitative data provided insight into the time of

day of an absence or absences. The time of day of an absence was crucial information in

determining if there were patterns during the school day. Each piece of data was needed in

determining if there were any patterns to the students who were chronically absent in school.

30

The quantitative data analysis provided an insight into the connection of Social Learning

Theory and chronic absenteeism. The Social Learning Theory implies that people learn from

one another by observing others, by imitating the behavior of others, and by behavior that is

modeled by others (Bandura, 1971). Chronic absenteeism is closely tied to Social Learning

Theory because students learn their attendance patterns through others and cognitive

development of themselves. As student’s progress through grade levels, the importance of peer

groups and social interactions with peer groups becomes more of an influence on students. At

the high school level, students were influenced by their peer groups and begin to imitate the

behavior around them. For some students, this will include being absent from classes.

Predictors of a students’ potential for a successful life after high school are comprised of

family identity, income, and choice of peer group. Perhaps if teachers and other school

personnel are aware of this phenomenon, being intentional about reaching out to all peer

groups could increase students’ feeling of welcome, and school attendance would

increase. (Hartnett, 2007, p. 36)

Problem Setting

The setting of the researcher’s problem of practice was at a ninth through twelfth grade

comprehensive high school in an urban setting in Arkansas. The school has approximately 2,700

students. High School X is the only high school in town of over 75,000 people. The town is

considered a college town, with a major university residing there. Based on these numbers and

percentages below in Table 3.1, chronic absenteeism is a concern at this high school.

31

Table 3.1

Chronically Absents During the Three Studied School Years

School Year Number Chronically Absent Percentage of Chronically Absent

2016-2017 773 28.7%

2017-2018 916 35.6%

2018-2019 1,142 44.2%

Note. These numbers represented partial day absences. A student qualified for this research

study when they were chronically absent from one or more classes in their class schedule.

During the past twelve years, the demographics at High School X have changed since the

researcher began working there, see table 3.2 below. During this time period, attendance rates

have also decreased and chronic absenteeism has also increased, as shown by Table 3.1, above.

Table 3.2

Demographic Information from 2008-2018

2008 2010 2012 2014 2016 2018

White 77% 75% 74% 73% 69% 67%

Hispanic 8% 9% 10% 10% 13% 13%

Black 9% 7% 10% 11% 11% 10%

Other Races 6% 7% 6% 6% 8% 9%

Free/Reduced Lunch 23% 26% 34% 34% 36% 31%

Special Education 11% 11% 11% 12% 12% 13%

During spring 2017, approximately 600 students were going to be denied credit in one or

more of their classes because of their attendance, or lack of attendance in classes. These students

accumulated more than eight absences in their credit-bearing classes, which meant they could be

denied credit in that class. When a student is denied credit for a class, they must retake that class

either through summer school or credit recovery, if the class is needed to graduate. By not

32

earning course credit, the student would also receive a failing grade in the class, which impacts

their overall high school grade point average. Chronic absenteeism is an issue at High School X,

and one that needs a solution to improve student attendance. When students do not receive

course credit, they have the possibility of not graduating on-time or not graduating at all.

Absenteeism is a concern that has been growing at High School X. When High School X

changed from a traditional seven-period day to a block schedule, both teachers and

administrators revised the attendance expectations for students to receive credit in a class. The

2016-2017 school year was the first year in which the new attendance standards were in place

with the new block schedule. The attendance expectations changed from thirteen absences to

nine absences for possible loss of credit. With this policy change, the number of students who

were eligible for losing credit increased significantly. Due to this concerning increase, there

were issues raised about students not graduating. Even with the new attendance policies, the

number of students who were chronically absent increased each year, while the researcher has

been employed at High School X.

Additionally, the school and school district have undergone major administrative

changes. In the five years since the block schedule was established, the school had three new

building principals and three new superintendents. The attendance policy for the high school and

school district has also changed three times during those five years. In each of these changes, the

expectations at High School X and the school district for attendance and how the school was

going to deal with attendance also fluctuated. With leadership changes, there were also changes

in the priority of items for school administration to prioritize. Due to these leadership and policy

changes, there has not been a consistency in expectations, messaging, or consequences for

students who were chronically absent in the three years studied.

33

Research Sample and Data Sources

The research data included approximately 2,700 students at High School X. The students

included in this research study were chronically absent students from the total student population

in ninth through twelfth grades during the 2016-2017, 2017-2018, and 2018-2019 school years.

These school years provided the archival data needed to provide a student sample of those who

were chronically absent. After reviewing the attendance data for High School X, the students

who were identified as chronically absent were students with nine or more absences in one or

more classes during the school year. High School X is on a block schedule, which requires each

class meet for 90 days within the school year. The standards imposed by the Arkansas

Department of Education require a student be chronically absent if they have missed 10% of the

school year, or nine days per class at High School X. The possible sample sizes for the studied

school years were 2016-2017 (773 students), 2017-2018 (916 students), and 2018-2019 (1,142

students). These students were the focus for this research sample. Some students from the 2017-

2018 school year were the same students in the 2018-2019 list of students who were chronically

absent. By identifying and analyzing the chronically absent students, it was crucial to have an

insight into the student characteristics of the chronic absences.

Data Collection Methods

The data collected for this research study was quantitative in nature. By using the

Arkansas Department of Education database Arkansas Public School Computer Network

(APSCN), the researcher found the number of absences for each student at High School X by

class period for the three designated school years for this research study analysis. The APSCN

system allowed the researcher to determine the students who were identified as chronically

absent with nine or more absences in one or more classes. The quantitative data collection relied

34

completely on the APSCN system for not only attendance information, but also demographic and

type of class the absence occurred. The APSCN system also pulled demographic information

such as race/ethnicity, Special Education (SPED) status, free and reduced lunch status, English

Language Learner (ELL) status, and grade level.

The type of class focused on the class being a core class such as English, Mathematics,

Science or Social Studies, or an elective. The type of class also provided information if it was

required for graduation. High school level students have the option to enroll in non-credit

classes such as teacher/office aide, study hall, and credit recovery. Each of these type classes do

not receive a grade; therefore, they do not count towards high school graduation. However, the

attendance in these classes was part of the information gathered in the quantitative stage of data

collection for this study.

Data Analysis Methods

To answer the research questions posed in this study, a non-experimental, correlational

quantitative design was utilized to guide the data analysis. After submitting and receiving

approval from the University of Arkansas Institutional Review Board and approval from the

school district, the analysis began with identifying the chronically absent students at High School

X. The COGNOS system is a report generator that pulls data from the APSCN system, where

teachers input their attendance information. A report from COGNOS was run to identify which

students were chronically absent by having missed nine or more days in a class. Next, a

COGNOS report was run to determine the student demographic information for those identified

as chronically absent. Each of these reports were compiled into multiple Excel spreadsheets.

The chronically absent students during the three school years focused on this study were first

analyzed using descriptive statistical analysis. A frequency distribution was used to describe the

35

details of the demographic information for chronically absent students. The demographic data

included grade level, race/ethnicity, SPED and ELL status, and free and reduced lunch

information. The demographic data was used to create frequency tables for the chronically

absent students per class period. The chronically absent student data was also used to create a

frequency distribution of the class period these students were missing as compared to the class

period absences from the entire school. This frequency distribution was then used to identify the

type of class these students were missing, such as core/non-core, graduation

requirement/elective, and non-credit/credit class. Each of these frequency distribution charts

were created for each school year that was analyzed in order to determine the data trends.

The data was also used to compare the students who were chronically absent to the

population of the entire school. This comparison was able to distinguish the differences between

these two groups, and determine if the chronically absent student followed the same trend as the

rest of the school. The class periods for Zero-Hour A and Zero-Hour B, and fourth and eighth

period were analyzed differently since not all students were enrolled in those classes. A student

at High School X takes 4 blocks of classes each day. If a student chooses to enroll in a Zero-

Hour class, that student does not take a fourth or eighth period class. Their four blocks would be

Zero-A, first period, second period and third period; therefore, their school day ends when third

period is complete on an A day. Or on a B day, the student would enroll in Zero-B, fifth period,

sixth period, and seventh period, and their school day would end with seventh period.

Trustworthiness

The quantitative data in this study was acquired from the Arkansas Department of

Education APSCN system. APSCN is the system the state of Arkansas uses to record data from

each individual school district; therefore, this data was considered true and reliable. The initial

36

quantitative data provided the list of students who were chronically absent. The quantitative data

provided an in-depth look at the characteristics of students who were chronically absent.

Trustworthiness includes ensuring validity and reliability. The concept of content validity is

primarily concerned with the notion that, “…the items measure the content they were intended to

measure” (Creswell, 2014, p. 160). The research was valid in its content since all students

chronically absent were included in the research data. The research study was reliable in its

results and findings because, another researcher could replicate the same research design by

using the same data points and populate the same results. The results were reliable because they

were based on valid collected school data. The trustworthiness of this study will be assured by

the replication by other researchers, the study could be reproduced and the outcome would be the

same.

The ethical issues surrounding this study revolved around two main areas of

concern. The first area of concern was working with data based on student attendance. This data

included the number of days a student was absent from school in a given semester, and the

number of absences per period. Students were absent for various reasons, and the school used a

coding system that protected the reason for an absence, if it was considered too personal. The

APSCN system uses a “PC” code to denote when a parent or guardian calls-in for a student

absence, which is considered an excused absence. If a parent or guardian calls in, no matter the

reason for the absence, a “PC” code is entered in the system. A “DOC” code is used when a

student brings supporting documentation for their absence. This documentation could be a note

from a doctor or court system, but only a “DOC” code is used in the system to show supporting

evidence to the school. A “U” code is used when a student has no reason for the absence, when a

parent has not called in, and no supporting documentation was provided to the school.

37

Therefore, this type of absence is unexcused. By using these three codes, the reason for an

absence is kept private when analyzing data for this study. The students in the dataset were

given a numerical value, which protected their identity, the use of the school codes, and the

nature of the absence to be given in general terms. The use of student data in a research study

can always present concern(s) or issue(s). The issue was how to protect the privacy of students

and their information in the research study. By using the school codes and a numerical

identification system, this issue was resolved in this research study.

The second area of concern was the researcher’s involvement at High School X. The

researcher has served on multiple committees to determine the new policy on student

attendance. These committees provided feedback to the district office in how the new attendance

policy was written and established. The ethical issue was removing any bias or opinions in

relation to the policy that could negatively impact this research study.

As previously discussed, the privacy of the students in the dataset was of upmost

importance. By using a numerical identification system rather than by student name, the

researcher has protected the privacy of student information. The second safeguard was using the

school coding when discussing the type of absence, which allowed an absence to be presented in

a generic and non-threatening manner. The personal nature of absences was removed from the

data, since the only data used were the “PC”, “DOC”, and “U” codes from the school

system. These codes allowed the researcher to determine the total number of absences and if

they were counted as an excused or unexcused absence. These safeguards ensured the privacy of

all data analyzed in this research study.

38

Limitations and Delimitations

Limitations

One limitation of this research study was the accuracy of the data from the APSCN data

network. This data is entered by people, and human error would be a limitation that would be

possible in this dataset. The data provided by each individual district and to the state is seen as

true and accurate data, so that is how it was used in the data analysis.

Another limitation to the research study was the availability of finding information about

the students who were dropped during the school year for lack of attendance. These students are

normally dropped if they have 10 or more days of consecutive absences. The data following

these specific students was not consistent. These students should be included in this research

study, but it will be difficult to find this specific data after they were dropped from High School

X.

Delimitations

The first delimitation of this study was to restrict the data collection to only one high

school in Arkansas. Due to the amount of data collected from the 2,700 students enrolled at

High School X during the three school years, this restriction provided a large group of student

data to be analyzed. The research study being restricted to one high school was necessary

because there is only one comprehensive high school within the school district. There are two

other high school campuses in the district, one is a School of Innovation with flexible attendance

requirements and the other is a completely virtual school, again with different attendance

requirements.

A second delimitation was restricting the research to the last five years. Five years ago,

there was a major shift in X Public Schools. These shifts involved the ninth grade being moved

39

from the junior high schools to the high school, zero-hour classes were added to the schedule,

multiple lunches were added to the schedule, and the campus was closed for students, and the

high school moved from a traditional seven-period day to a four-period day block schedule.

These major changes created a natural split in information that was used in this research study.

With the unprecedented closing of traditional school settings in spring 2020 because of the

COVID-19 virus, the 2019-2020 school year was not included in this research study. Due to the

continuation of COVID-19, there were school restrictions and unexpected mandatory student

quarantines, which led to the 2018-2019 school year being the last year included in the research

study.

Summary

The non-experimental, correlational quantitative design provided the guidelines for

collecting and analyzing the data needed to answer the research questions regarding chronic

absenteeism. This method of research for analyzing the quantitative data was used to determine

“…whether and to what degree a statistical relationship exists between two or more variables”

(Mertler, 2019, p. 101).

40

CHAPTER FOUR: RESEARCH ANALYSIS AND RESULTS

Introduction

The purpose of this study was to provide insight and understanding of the chronically

absent students and their common characteristics at High School X. This chapter was used to

present the results of the research study and analyze those results (Bloomberg & Volpe, 2016).

The data used in this study was archival data from the 2016-2017, 2017-2018, and 2018-2019

school years at High School X. The archival data included demographic information such as

race/ethnicity, SPED and/or ELL status, free and reduced lunch status, and grade level. The

archival data also included information on the type of class, core class such as English,

Mathematics, Science or Social Studies, or an elective. The type of class also described the

classes that were required for graduation and those that were not required for graduation. High

school students will sometimes enroll in non-credit classes such as teacher/office aide, study hall,

or credit recovery. Chapter Four is organized by answering the two research questions and the

sub-categories of those research questions. The first research question was related to

demographic information, the demographic subcategory information include grade, ethnicity,

lunch status, and SPED and ELL. The demographic information was disaggregated for the three

school years that were the focus for this research study. The second research question was

focused on the understanding of the class, with the chronic absence. The subcategories for this

research question included the subject matter of the class, the department the subject matter

resides, if the class was a core class, elective, or non-credit class, and what time of day did that

class period fall during the school day. Again, this information was disaggregated over three

school years 2016-2017, 2017-2018, and 2018-2019 at High School X. The research questions

being answered by the archival data were:

41



2. What are the correlations, if any, among students’ chronic absenteeism and the class

period of the absence?

The beginning of Chapter Four provided the descriptive statistics of the three identified school

years of absenteeism which was the focus for this research study. The second section of Chapter

Four provided insight into the correlation of demographic information and chronically absent

students. The last section of Chapter Four provided insight into the correlations of chronically

absent students and the class period, or subject matter where they were chronically absent.

Quantitative Data Results

The non-experimental, correlational quantitative design provided the guidelines for

collecting and analyzing the data needed to answer the research questions concerning chronic

absenteeism. The 2016-2017, 2017-2018, and 2018-2019 school years provided the dataset

information on the chronically absent identified students at High School X. The information

presented in Table 4.1 represents the total students enrolled and the total students considered

chronically absent in one or more classes at High School X. Chronic absenteeism was defined as

a student missing nine or more classes in a school year. By the definition of chronically absent, a

significant percentage of students were chronically absent in one or more classes in each studied

school year, 2016-2017 (28%), 2017-2018 (34%), and 2018-2019 (42%).

42

Table 4.1

Percentage of Chronically Absent Students by School Years

School Year Chronically

Absent Student

Total Students

Enrolled

Percent of students

Chronically Absent

2016-2017 757 2,690 28%

2017-2018 871 2,574 34%

2018-2019 1,078 2,586 42%

Table 4.2 represents the students who were chronically absent and the total number of students in

comparison by grade level. During the 2016-2017 and 2017-2018 school years, twelfth grade

students had the highest percentage of chronically absent students. In the 2018-2019 school

year, 44% of ninth grade students were chronically absent, which was 8% higher than twelfth-

grade students during that same school year. The percentages found in Table 4.2 represent the

percentage of students who were chronically absent by grade-level in comparison to the total

number of students who were in that grade-level. During the 2017-2018 school year, 37% of the

twelfth-grade students were considered chronically absent from one or more classes.

Table 4.2

Chronically Absent Students by Grade Level

2016-2017 2017-2018 2018-2019

Grade Level Chronic

Absence

Total

Students Percent

Chronic

Absence

Total

Students Percent

Chronic

Absence

Total

Students Percent

9th grade 132 753 18% 205 780 26% 308 705 44%

10th grade 156 711 22% 213 736 29% 282 779 36%

11th grade 221 731 30% 191 690 28% 231 742 31%

12th grade 248 705 35% 262 704 37% 257 710 36%

Demographic Information

The first research question asked, what correlation, if any, does demographic information

have with students’ chronic absenteeism at High School X? The archival data provided insight

into the demographic information for the students who were chronically absent in comparison to

43

students who were not chronically absent. The number of students who were chronically absent

by race is displayed in Figure 4.1. Based on the data, Black, Hispanic or Latino, two or more

races, and white races had increases in chronic absenteeism, over the three-year time period.

Figure 4.1. Race demographic information for chronically absent student over three years.

The following information in Table 4.3 provided a comparison of race by school years with the

students who were chronically absent, as compared to the total students in each of those race

demographic categories. The percentage represents the percent of students who were chronically

absent within each sub-category of race. In 2016-2017, 28% of the Hispanic or Latino

population were chronically absent. Based on the data analysis, it was found slightly over one in

four Hispanic or Latino students were considered chronically absent in one or more classes.

25 7

8

4

10

4

4 33

50

9

26 7

7

4

11

7

2 38

60

7

22

11

5

5

13

8

2

64

73

2

NU

MB

ER O

F ST

UD

ENTS

RACE

2016-2017 2017-2018 2018-2019

44

Table 4.3

2016-2017 Race Comparison

Race Chronically

Absent Total

Percentage CA by

Sub-Population

Asian 25 95 26%

Black 78 308 25%

Hawaii/Pacific Islander 4 20 20%

Hispanic or Latino 104 369 28%

Native American/ Alaskan Native 4 20 20%

Two or More Races 33 92 36%

White 509 1,980 26%

During the 2017-2018 school year, the total percentage of students who were Hispanic or Latino

sub-category rose to 35% as shown in Table 4.4. This archival data indicated slightly over one

in three Hispanic or Latino students were chronically absent in one or more classes. In each of

the race sub-categories except Native American/Alaskan Native, the percentage of students grew

from the previous year.

Table 4.4


Race Chronically

Absent Total

Percentage CA by

Sub-Population

Asian 26 100 26%

Black 77 246 31%




45

Table 4.4 (Cont.)

Race Chronically

Absent Total

Percentage CA by

Sub-Population


White 607 1764 34%

During the 2018-2019 school year, 41% of Hispanic or Latino students were chronically absent.

In Table 4.5, the 2018-2019 school year data showed the student sub-category of two or more

races with 50% of the students being chronically absent. This proved that half of the students in

this category missed nine or more classes in at least one subject matter for the school year.

Table 4.5


Race Chronically

Absent Total

Percentage CA by

Sub-Population

Asian 22 93 24%

Black 115 263 44%





White 732 1,739 42%

Table 4.6 provides information on the students who have an IEP and receive Special Education

services and the students who are English Language Learners. Forty-one percent of the special

education students were chronically absent during the 2017-2018 school year. Forty-two percent

of English Language Learners were chronically absent in the 2018-2019 school year.

46

Table 4.6

Chronically Absent Student Identified by ELL or SPED

2016-2017 2017-2018 2018-2019

Chronic

Absence

Total

Student Percentage

Chronic

Absence

Total

Student Percentage

Chronic

Absence

Total

Student Percentage

ELL 73 231 32% 68 180 38% 76 181 42%

SPED 57 346 16% 127 308 41% 180 336 54%

Table 4.7 represents each of the demographic categories that were analyzed in the 2016-2017

school year. The first column represents the percentage of students who were chronically absent

in each of the demographic sub-categories. In 2016-2017, 26% of the White students were

chronically absent. The second column represents the percentage of the chronically absent

demographic sub-category, in comparison to the total amount of students chronically absent.

Chronically absent Black students were 10% of the total population of students who were

chronically absent. The last column represents the demographic sub-category in terms of the

total student population. In the 2016-2017 school year, 26% of the student body was made up of

ninth grade students.

Table 4.7

2016-2017 Analysis by Demographics

Race Chronically

Absent Total

CA/Total Sub-

Population

CA/Total

CA

Total Sub-

Pop/Total Pop

Asian 25 95 26% 3% 3%

Black 78 308 25% 10% 11%

Hawaii /

Pacific

Islander

4 20 20% 1% 1%

Hispanic or

Latino 104 369 28% 14% 13%

Native

American /

Alaskan

Native

4 20 20% 1% 1%

47

Table 4.7 (Cont.)

Race Chronically

Absent Total

CA/Total Sub-

Population

CA/Total

CA

Total Sub-

Pop/Total Pop

White 509 1,980 26% 67% 69%

9th grade 132 753 18% 17% 26%

10th grade 156 711 22% 21% 25%

11th grade 221 731 30% 29% 25%

12th grade 248 705 35% 33% 24%

ELL 73 231 32% 10% 8%

SPED 57 346 16% 8% 12%

Free/Reduced

Lunch 273 1038 26% 25% 35%

Table 4.8 represents the demographic sub-categories for the student population and chronically

absent students during the 2017-2018 school year. The percentage columns in Table 4.8

represent the same breakdown of information as in Table 4.7. The twelfth-grade class

represented 30% of the chronically absent population, and 24% of the total student population

for the 2017-2018 school year.

Table 4.8


Race Chronically

Absent Total

CA/Total Sub-

Population

CA/Total

CA

Total Sub-

Pop/Total Pop

Asian 26 100 26% 3% 4%

Black 77 246 31% 9% 10%

Hawaii /

Pacific

Islander

4 15 27% 0% 1%

Hispanic or

Latino 117 334 35% 13% 13%

48

Table 4.8 (Cont.)

Race Chronically

Absent Total

CA/Total Sub-

Population

CA/Total

CA

Total Sub-

Pop/Total Pop

Two or More

Races 38 100 38% 4% 4%

White 607 1,764 34% 70% 69%

9th grade 205 780 26% 24% 27%

10th grade 213 736 29% 24% 25%

11th grade 191 690 28% 22% 24%

12th grade 262 704 37% 30% 24%

ELL 68 180 38% 8% 6%

SPED 127 308 41% 15% 11%

Free/Reduced

Lunch 301 822 37% 35% 28%

Table 4.9 represents the demographic sub-categories for the student population and chronically

absent students during the 2018-2019 school year. The percentage columns in Table 4.9

represent the same breakdown of information as in Table 4.7 and 4.8. The twelfth-grade class

represented 36% of the chronically absent population, and 24% of the total student population

for the 2018-2019 school year.

Table 4.9


Race Chronically

Absent Total

CA/Total Sub-

Population

CA/Total

CA

Total Sub-

Pop/Total Pop

Asian 22 93 24% 2% 4%

Black 115 263 44% 11% 10%

Hawaii /

Pacific

Islander

5 13 38% 0% 1%

49

Table 4.9 (Cont.)

Race Chronically

Absent Total

CA/Total Sub-

Population

CA/Total

CA

Total Sub-

Pop/Total Pop

Hispanic or

Latino 138 335 41% 13% 13%

Native

American /

Alaskan

Native

2 13 15% 0% 1%

Two or More

Races 64 129 50% 6% 5%

White 732 1,739 42% 68% 67%

9th grade 308 705 44% 29% 24%

10th grade 282 779 36% 26% 27%

11th grade 231 742 31% 21% 25%

12th grade 257 710 36% 24% 24%

ELL 76 181 42% 7% 6%

SPED 180 336 54% 17% 11%

Free/Reduced

Lunch 416 1038 40% 39% 35%

In Figure 4.2, this chart presents the results of the special education students who were

chronically absent during the three school years and also the student’s lunch status. During the

2018-2019 school year, 180 special education students were chronically absent from one or more

courses. and 120 (67%), also qualified for free/reduced lunches. The number of special

education students who were chronically absent and on free/reduced lunch status were 2016-

2017 (65%), 2017-2018 (63%), and 2018-2019 (67%).

50

Figure 4.2. Chronically absent special education student’s lunch status.

Class Period and Subject Matter Information

The second research question asked, what are the correlations among students’ chronic

absenteeism and the class period of the absence? This question focused on the particular time of

day of an absence for the students who were chronically absent. The question also analyzed the

class subject matter that chronically absent students were missing. High School X was on a

block schedule during the 2016-2017, 2017-2018, and 2018-2019 school years. Within this

block schedule, students had the option of taking a Zero-Hour class on either the A day or B day,

or both. If a student chose to take a Zero-Hour class, their class day started at 7:15 am and ended

at 2:15 pm. These students were not enrolled in the last period of the day on an A day, which

was fourth period and on a B day that was eighth period. During the day, lunches occurred

during second period and sixth period. In Table 4.10, it provides a breakdown of students who

were chronically absent by class period, and compares those absences to the total number of

students enrolled in that class period. In Table 4.10, it shows that Zero A class had 19.7%,

0

20

40

60

80

100

120

140

160

180

200

2016-2017 2017-2018 2018-2019

Chronically Absent Special Education students

FRL Non-FRL

51

22.5%, and 26.1% of the students enrolled in that class period were chronically absent in all

three school years. The Zero B day period in 2018-2019 showed 27.6% of the students enrolled

in the class were chronically absent. Chronic absenteeism is defined when a student missed nine

or more classes during a school year.

Table 4.10

Chronic Absenteeism by Class Period

2016-2017 2017-2018 2018-2019

Class

Period

Total

CA

Total

Students

in Period

Percent

CA/Total

in class

period

Total

CA

Total

Students

in Period

Percent

CA/Total

in class

period

Total

CA

Total

Students

in Period

Percent

CA/Total

in class

period

ZA 117 595 19.7% 139 618 22.5% 170 652 26.1%

1st 284 2,495 11.4% 310 2,428 12.8% 428 2,433 17.6%

2nd 298 2,495 11.9% 314 2,432 12.9% 465 2,421 19.2%

3rd 315 2,498 12.6% 377 2,425 15.5% 496 2,417 20.5%

4th 337 1,914 17.6% 349 1,789 19.5% 477 1,754 27.2%

ZB 93 487 19.1% 113 490 23.1% 162 588 27.6%

5th 294 2,489 11.8% 350 2,425 14.4% 429 2,423 17.7%

6th 301 2,498 12.0% 373 2,423 15.4% 459 2,393 19.2%

8th 353 2,022 17.5% 375 1,930 19.4% 478 1,825 26.2%

Table 4.11 provides information on the chronically absent students by subject matter and class

period for the 2016-2017 school year. The table represents all classes which had a chronically

absent student enrolled for the 2016-2017 school year. English 12 had the highest number of

students who were chronically absent with 86 total students.

52

Table 4.11

Number of Students Chronically Absent by Subject Matter and Class Period in 2016-2017

Subject ZA 1st 2nd 3rd 4th ZB 5th 6th 8th Total by

Subject Matter

A Cappella Year 3 3* 3


Adv Topics &

Modeling Math 6* 6

Advanced Audio/Vis

Tech/Film 2 2

Advanced Television 3 1 4

Agri Structural

Systems 4* 4

Agricultural

Marketing 2 2

Agricultural

Mechanics 8 8 16

Agricultural Metals 6 7 8 21

Algebra I 5 4 1 10 5 2 8 35

Algebra II 5 7 1 9 10 10 1 10 53

Algebra III 9 9 3 16 8 2 14 61

Algebra Lab 1 1

American History 7 14 10 5 6 7 6 55

Anatomy/Physiology 2 5 3 10

Animal Science II 2 2

AP Art History 2 2 4

AP Biology 1 3 6 10

AP Calculus AB 2 2 2 2 3 11

53

Table 4.11 (Cont.)


Subject Matter

AP Calculus BC 1 1

AP Chemistry 3* 3

AP Computer

Science 3* 3

AP Computer

Science Principles 1 2 3

AP Environmental

Science 5* 5

AP European History 2 4 6

AP French Language 1 1

AP Human

Geography 1 2 1 4 4 2 14

AP Lang Comp 13 5 2 9 5 1 35

AP Lit 5 4 2 4 4 3 6 28

AP Music Theory 2 5 7

AP Physics C 1 1

AP Physics I 3 1 2 6

AP Psychology 3 8 5 3 2 21

AP Spanish

Language 1 1

AP Statistics 1 2 3

AP Studio Art 2 2

AP US Government

& Politics 5* 5

AP US History 3 1 1 5

AP World History 2 3 2 6 1 3 17

54

Table 4.11 (Cont.)


Subject Matter

Art 3D 3* 3

Art I 9 4 17 3 2 13 48

Art II 3 4 2 9

Art III 3* 3

Band I 2 1 3

Band II 1 1

Band III 3 3 6

Band IV 1 4 5

Banking & Finance

Principles 2 2

Biology 2 5 3 9 2 2 13 3 14 53

Bridge Algebra II 1 5 6

Bridge to Algebra II 4 1 3 8

Ceramics I 9 2 6 3 7 6 33

Cheerleading

Gametime 4* 4

Chemistry 6 8 5 8 5 8 4 44

Civics 3* 3

Computer

Applications I 1 1

Computer

Applications II 1 1 1 1 4

Computer Science

Essentials 3 3 6

55

Table 4.11 (Cont.)


Subject Matter

Concert Choir Year 2 4* 4

Concert Choir Year 3 2 2

Concurrent Social

Studies 1 1

Contemporary US

History 3* 3

Cosmetology I 1 1

Cosmetology Lab 1 1

Costume Design &

Tech 4* 4

Creative Writing II 4* 4

Credit Recovery 3 1 5 2 2 7 1 21

Critical Reading 1 4 5

Cultural Studies 3 10 2 5 7 5 32

Dance Gametime 2 2

Dawg Crew Service

Learning 2 2

Debate II 3* 3

Debate III 2 2

Digital Electronics 4* 4

Digital Learning 2 1 3 1 7

Digital Learning

Virtual Arkansas 1 1

56

Table 4.11 (Cont.)


Subject Matter

E.A.S.T. I 1 2 2 5

E.A.S.T. II 2 2

Economics 4 8 7 4 3 26

English 8 4 1 13

English 10 3 8 6 2 19 2 2 5 47

English 11 7 11 9 12 11 1 23 74

English 12 6 13 10 11 2 14 7 23 86

English 9 1 6 6 4 8 7 32

English Comp I 1 1

English Comp II 2 2

Environmental

Science 3 7 1 4 1 6 8 30

ESL I 3* 3

ESL II 1 1

Family & Consumer

Science 1 8 8 6 11 34

Fashion

Merchandising 1 3 2 9 15

FHS Ambassador

Service Learn 1 1

Financial Literacy 3 6 1 1 2 13

Food Nutrition 3 2 3 7 2 17

Football / Freshman 6* 6

57

Table 4.11 (Cont.)


Subject Matter

Forensics II 1 1

French I 1 4 2 7

French II 1 2 1 2 6

French III 2 2

French IV 3* 3

Fund Audio Visual

Tech/Film 4 2 2 8

Fundamentals of

Television 1 3 2 6

Fundamentals

Photography 2 4 4 5 15

Geometry 3 3 1 6 5 2 10 30

Geometry 10 4 3 1 1 9

German I 2 2

German II 5 6 11

German IV 1 1

Greenhouse

Management 5* 5

Health & Wellness 2 2 7 4 7 10 1 33

History 2 3 5

Housing Interior

Design 6 1 6 3 16

Human Relations 9 8 17

Intermediate Aud/Vis

Tech/Film 5 2 7

58

Table 4.11 (Cont.)


Subject Matter

Intermediate

Photography 2 2

Intermediate

Television 1 2 3

Intro to Engineering

Design 3 2 5

Journalism I 2 2

Journalism II

Newspaper 2 2

Journalism III

Newspaper 1 1

Journalism IV

Newspaper 2 2

Journalism IV

Yearbook 1 1

Library Community

Service 1 1 1 3

Life Skills 1 4 5

Linear

Systems/Statistics 5 5 10

Literary Mag

I/Creative 2 2

Literary Magazine III 1 1

Marketing 3 7 8 18

Marketing

Management 3 3

Math 7 5 12

Math 11 1 1

Media Comm A/V

Tech-Film Lab 1 1

59

Table 4.11 (Cont.)


Subject Matter

Men Choir Year 2 1 1


Men’s Tennis 4* 4

NWTI Concurrent 0B

- 5 period 1 1

OC/Forensics I 2 2

Office Aide 2 1 2 3 2 2 2 14

Oral Comm 7 11 4 8 5 8 7 50

Orchestra III 1 1

Orchestra IV 3 3

Orientation to

Teaching 4 7 11

Outdoor Ed/Env

Science 2 10 12

Outdoor Education

PE 7 4 11

Parenting 4 5 5 14

Physical Education 8 5 13

Physical Education

Boys 9 2 3 5

Physical Education

Girls 9 2 2 4

Physical Education

Semester 7 13 5 25

Physical Science 4 6 4 7 7 8 36

Physical Science 9 2 2

Physics 1 8 5 4 4 22

Pre AP Algebra I 1 7 5 13

60

Table 4.11 (Cont.)


Subject Matter

Pre AP Algebra II 1 2 1 4 1 2 11

Pre AP Biology 2 2 6 4 3 1 5 23

Pre AP Chemistry 3 1 1 5 1 3 14

Pre AP Eng 10 5 6 2 4 1 8 26

Pre AP English 9 3 1 3 1 2 4 1 15

Pre AP Geometry 2 4 2 4 7* 19

PreCalculus 3 1 4 5 6 19

Principles Ag Science

Plant 4* 4

Principles of

Engineering 2 2 1 5

Psychology 9 5 3 7 24

Science 4 5 9

Service Learning

STUCO 4* 4

Small Engine

Technology 5* 5

Social Studies 1 2 1 1 5

Sociology 2 8 8 9 12 39

Spanish for Native

Speakers I 1 1

Spanish for Native

Speakers II 1 1

Spanish I 1 1 2 5 1 9 19

Spanish II 4 2 3 8 2 6 25

Spanish III 3 2 1 6 4 16

61

Table 4.11 (Cont.)


Subject Matter

Spanish IV 2 5 7

Sports Med Injury

Assessment 3 2 1 6

Sports Medicine

Foundations 8 2 3 6 1 20

Stagecraft I 1 1 2

Street Law 8 1 9

String Orchestra I 1 1

Survey Agricultural

Systems 9 3 3 4 19

Teacher Aide 5 5 7 6 9 1 8 17 8 66

Team Baseball 5* 5

Team Cross Country 6* 6

Team Dance JV 6* 6

Team Football 7* 7

Team Golf 5* 5

Team Soccer Men 4* 4

Team Soccer Women 1 1

Team Softball 2 2

Team Swimming 1 1

Team Tennis Women 4* 4

Team Track 16* 16

Team Volleyball 5* 5

62

Table 4.11 (Cont.)


Subject Matter

Team Wrestling 2 2

Television Lab 2 2

Theatre Appreciation 9 10 12 6 37

Theatre I 2 2

Theatrical Makeup 4 10 14

Track / Freshman 1 2 3

Transitional English

12 1 1

Transitional Math

Ready 7 6 13

Transitions 5 1 6

Vocal Music JV

Women 9 4* 4

Vocal Music Varsity

Men 9 1 1

Vocal Music Varsity

Women 9 1 1

Volleyball /

Freshman 1 1

Winter Guard 3* 3

Women Choir Year 2 3* 3

Women Choir Year 3 2 2

World Geography 4 1 7 3 15

World History 10 11 10 15 6 9 13 10 84

Total by class period 107 268 287 288 320 93 279 272 341 2,255

Note: Outliers: Bold numbers represent individual classes whose period chronic absenteeism is at

least 33% higher than other classes. Numbers with * represent classes only provided one period

in the schedule whose chronic absenteeism is at least 33% higher.

63

Table 4.12 provides information on the chronically absent students by subject matter and class


absent student enrolled for the 2017-2018 school year. English 12 had the highest number of

students who were chronically absent with 87 total students.

Table 4.12

Number of Students Chronically Absent by Subject Matter and Class Period in 2017-2018


Subject Matter

11/12 ELD 1 1 1

9 ELD 2 1 1

A Cappella Year 3 1 1


Advanced Audio/Vis

Tech/Film 1 1 2

Agri Structural

Systems 8 5 13

Agricultural Business 5* 5

Agricultural

Mechanics 3 8 11


Agricultural Power

Systems 1 1

Algebra I 5 2 5 13 2 13 12 52

Algebra I Part B 1 1

Algebra II 3 5 6 13 6 4 12 1 5 55

Algebra III 4 2 1 5 5 7 3 1 28

Algebra Lab 1 2 3


64

Table 4.12 (Cont.)


Subject Matter


Animal Science II 5* 5

AP Art History 4* 4

AP Biology 1 1 4 6

AP Calculus AB 2 2 1 1 6

AP Calculus BC 1 1 2

AP Chemistry 1 1 2

AP Comparative

GovrnmntPolitic 2 2

AP Computer Sci

Principles II 2 2

AP Computer

Science A II 2 2

AP Environmental

Science 2 11 13

AP European History 2 2

AP French Language 2 2

AP German

Language 3* 3

AP Human

Geography 4 2 7 13

AP Lang Comp 4 6 3 3 7 23

AP Lit 3 1 2 11 4 9 30

AP Microecon

Personal Finance 5 1 6

AP Music Theory 2 2

AP Physics I 1 2 3

65

Table 4.12 (Cont.)


Subject Matter

AP Psychology 2 2 9 6 6 4 29

AP Spanish

Language 4 1 5

AP Statistics 6* 6

AP Studio Art 2 2

AP US Government

& Politics 3 4 5 12

AP US History 1 3 1 7 12

AP World History 4 2 2 1 3 12

Art History:

Prehistoric 1 1

Art I 7 6 7 2 3 6 31

Art II 4 4 8

Art III 3* 3

Band I 2 3 5

Band II 5* 5

Band III 1 1

Band IV 3 3 6

Basketball Freshman/

Men 2 2

Basketball Freshman/

Women 2 2

Biology 6 10 6 3 9 7 4 11 56

Biology Alternate

Assessment 2 2

Bridge Algebra II 2 1 3 3 9

66

Table 4.12 (Cont.)


Subject Matter

Bridge to Algebra II 2 2 1 1 6

Careers in Criminal

Justice 1 1

Ceramics I 3 4 4 7 9 6 3 5 7 48

Ceramics II 2 1 3

Cheerleading

Gametime 1 1

Chemistry 6 5 7 2 3 1 12 5 41

Chinese I 1 1

Civics 1 3 4

Civil

Engineering/Architec

ture

3* 3

College Algebra 1 1 2

Computer

Applications I 2 3 1 6

Computer

Applications II 1 1 1 3

Computer

Applications III 1 1

Computerized

Accounting I 1 1



Costume Design &

Tech 3* 3

Creative Writing II 5* 5

Credit Recovery 2 4 1 3 1 6 4 4 25

Critical Reading 1 1 2 4

67

Table 4.12 (Cont.)


Subject Matter

Cultural Studies 11 3 5 19

Dance Gametime 8* 8

Dave Ramsey

Finance 1 1

Dawg Crew Service

Learning 7* 7

Debate I 2 3 5

Debate III 2 2

Digital Electronics 4* 4

Digital Learning 3 4 7

Digital Learning ECE 2 2 1 1 6

Digital Learning

FVA 1 4 7 4 16

Digital Learning

Virtual 1 1 1 1 4

Digital Learning

Virtual Arkansas 1 1

Drawing I 4 11 4 4 23

E.A.S.T. I 3 4 7

E.A.S.T. II 1 1

Early Childhood

Education 1 1

Earth Space Science 1 1

Economics 4 1 3 3 4 3 2 20

English 4 5 6 2 17

English 10 4 5 7 11 20 2 5 7 5 66

68

Table 4.12 (Cont.)


Subject Matter

English 11 6 9 8 1 13 6 12 9 7 71

English 12 5 9 13 2 16 15 15 10 2 87

English 9 10 8 11 8 11 48

English Comp I 1 1 2

English Comp II 4 5 9

Environmental

Science 4 7 2 6 1 7 6 33

Family & Consumer

Science 6 2 6 6 4 10 34

Fashion

Merchandising 9 1 2 12

FHS Ambassador

Service Learn 4* 4

Financial Literacy 1 4 2 7

Finite Math 2 2

Food Nutrition 18 1 1 1 1 22

Football / Freshman 8* 8

Forensics II 1 1

Forensics III 2 2

French I 5 2 2 9

French II 4 2 2 8

French III 3 3 6

French IV 1 1

Fund Audio Visual

Tech/Film 1 3 2 6

69

Table 4.12 (Cont.)


Subject Matter

Fundamentals of

Television 3 3 6

Fundamentals

Photography 2 7 6 15

FYI Freshman Intro 1 1 1 3

Game Design

Programming I 1 1 2

Game Design

Programming II 4 4 8

Geometry 2 7 7 1 8 4 12 41

Geometry 10 2 3 2 8 3 18

German I 1 3 4

German II 3* 3

German III 2 2

German IV 1 1

Greenhouse

Management 2 2

Health & Wellness 5 12 5 4 6 6 1 39

Health Science 1 1 1

Housing Interior

Design 5 3 2 3 13



Tech/Film 1 1

Intermediate

Photography 1 1 2

Intermediate

Television 1 1


Design 1 3 2 6

70

Table 4.12 (Cont.)


Subject Matter

J. A. G. 2 4 5 11

JAG Apprenticeship 6 1 8 15

Journalism I 2 6 8

Journalism II

Newspaper 1 1

Journalism II

Yearbook 1 1

Journalism III

Yearbook 1 1

Library Community

Service 1 1 2

Life Skills 3 1 4

Linear

Systems/Statistics 2 7 9

Literary Magazine III 3* 3

Marketing 2 2

Marketing

Management 2 2

Math 2 3 5 8 3 21

Men’s Tennis 2 2

NWACC NTI P-8

E1E2 Bday 1 1

OC/Forensics I 2 2

Office Aide 1 4 5

On The Job Training 1 1 2 2 6

Oral Comm 6 5 2 14 10 5 7 11 20* 80

Orientation to

Teaching 4 6 10

71

Table 4.12 (Cont.)


Subject Matter

Outdoor Ed/Env

Science 6 6 12

Outdoor Education

PE 9 8 17

Parenting 5 2 6 3 4 20

PE 9 3 12

Personal Fitness For

Life 2 2 10 14

Philosophy 1 1 2

Physical Education 3 6 9

Physical Education

Boys 9 3 4 4 11

Physical Education

Girls 9 3 2 2 7

Physical Education

Semester 13 13

Physical Science 6 8 10 6 12 1 7 50

Physical Science 9 1 3 1 1 6

Physics 5 5 4 5 19

Pre AP Algebra I 2 8 2 1 13

Pre AP Algebra II 1 1 10 3 6 7 28

Pre AP Biology 1 2 4 3 2 2 14

Pre AP Chemistry 2 1 1 1 2 4 2 13

Pre AP Eng 10 4 5 8 2 4 3 26

Pre AP English 9 2 9 9 5 25

Pre AP Geometry 2 1 6 6 5 5 1 4 30

72

Table 4.12 (Cont.)


Subject Matter

Pre AP Physical

Science 3 3 2 8

PreCalculus 2 1 1 4 3 1 12

Principles Ag Science

Plant 5* 5

Principles of

Engineering 1 1 2

Principles of Public

Service 1 1

Psychology 3 6 1 5 15

Quantitative Literacy 2 10 12

Science 1 12 2 2 17

Service Learning

STUCO 2 2

Small Business

Operations 5* 5

Small Engine

Technology 7 6 13

Social Media I 3 1 1 5

Social Studies 9 1 4 4 2 20

Sociology 3 8 3 6 10 30

Spanish for Native

Speakers I 2 2

Spanish for Native

Speakers II 3* 3

Spanish I 1 1 3 3 5 2 15

Spanish II 3 5 5 8 3 4 1 29

Spanish III 2 3 1 2 2 5 15

Spanish IV 2 3 5

73

Table 4.12 (Cont.)


Subject Matter

Sports Med Injury

Assessment 4 7 11

Sports Medicine

Foundations 5 6 10 21

Stagecraft I 3 4 4 2 6 19

Street Law 8* 8

String Orchestra I 3* 3

Study Hall 1 1

Survey Agricultural

Systems 7 6 4 17

Teacher Aide 4 9 5 11 5 5 9 22 10 80

Team Baseball 4 4

Team Basketball Men 1 1

Team Cheer JV 2 2

Team Cross Country 2 2

Team Dance JV 5* 5

Team Dance Varsity 4* 4

Team Football 8* 8

Team Golf 2 2

Team Soccer Men 3* 3

Team Soccer Women 2 2

Team Softball 1 1

Team Swimming 2 2

74

Table 4.12 (Cont.)


Subject Matter

Team Tennis Women 5* 5

Team Track 25* 25

Team Volleyball 1 1

Team Volleyball

/Sophomore 3* 3

Team Wrestling 4* 4

Television Lab 1 1

Theatre Appreciation 6 6 15* 27

Theatre I 1 1

Theatre II 1 1

Theatre III 2 2


Track / Freshman 2 2


12 1 1

Transitional Math

Ready 5 7 12

Transitions 1 1

US History 1 1 1 3

Veterinary Science 2 2

Visual Art

Appreciation 6 4 6 16

Vocal Music JV

Women 9 8* 8

Vocal Music Varsity

Men 9 2 2

75

Table 4.12 (Cont.)


Subject Matter

Vocal Music Varsity

Women 9 4* 4

Winter Guard 3* 3



Women Choir Year 4 1 1

World Geography 3 2 3 8

World History 13 11 12 6 9 11 62

Wrestling freshmen 1 1

Total 139 310 314 377 349 113 350 373 375 2,700




Table 4.13 provides information on the chronically absent student by subject matter and class


absent student enrolled for the 2018-2019 school year. American History had the highest

number of students who were chronically absent with 108 total students. English 12 had 61 total

students who were chronically absent.

76

Table 4.13

Number of Students Chronically Absent by Subject Matter in 2018-2019


Subject Matter



ACT/PSAT/SAT

Test Prep 1 1 1 4 7

Advanced Audio/Vis

Tech/Film 1 1

Advanced

Photography 2 2

Agri Structural

Systems 2 9 11

Agricultural Business 7* 7

Agricultural

Electricity 1 1

Agricultural

Mechanics 5 6 11


Agricultural Power

Systems 2 2

Algebra I 2 6 2 4 3 5 22

Algebra I Part B 2 3 2 1 8

Algebra II 7 8 2 12 11 9 5 6 5 65

Algebra III 7 4 6 13 6 6 42

Algebra Lab 1 1



Animal Science 2 3 6 11

77

Table 4.13 (Cont.)


Subject Matter

AP Art History 5* 5

AP Biology 3 3 3 9

AP Calculus AB 5 1 2 2 10

AP Calculus BC 5* 5

AP Chemistry 1 2 3 6

AP Comparative

GovrnmntPolitic 1 1

AP Computer

Science A II 3* 3

AP Computer

Science Principles II 2 2

AP Environmental

Science 2 3 5

AP European History 3* 3

AP German

Language 1 1

AP Human

Geography 5 3 4 4 16

AP Lang Comp 4 4 4 4 3 3 5 2 3 32

AP Lit 6 3 3 12

AP Microecon

Personal Finance 3 2 5

AP Music Theory 1 1

AP Physics 1 2 2

AP Physics 2 2 2

AP Psychology 5 3 6 1 2 17

AP Spanish

Language 3* 3

78

Table 4.13 (Cont.)


Subject Matter

AP Statistics 4 11 3 18

AP Studio Art 1 1

AP US Government

& Politics 1 5 10 16

AP US History 4 6 5 2 2 19

AP World History 2 2 3 4 2 13

Art History:

Prehistoric 1 1

Art I 8 3 11

Art II 3 1 4 8

Art III 3* 3

Basketball Men 2 2

Basketball Men 9 2 2

Basketball Women 2 2

Basketball Women 9 1 1

Biology 3 3 2 3 11

Biology Alternate

Assessment 1 1 2

Bridge Algebra II 2 2 2 5 11

Bridge to Algebra II 2 3 5 3 13

Ceramics I 6 5 3 8 11 6 4 6 49

Ceramics II 1 1 2

Cheer Gametime 1 1

79

Table 4.13 (Cont.)


Subject Matter

Cheer JV 1 1

Cheer Varsity 9* 9

Cheerleading

Gametime 4* 4

Chemistry 2 1 3

Chemistry -

Integrated 7 11 1 3 12 3 4 6 47

Child Development

& Parenting 3 6 10 8 5 5 18 55

Civics 2 2 1 5

Civil

Engineering/Architec

ture

1 1

Comp Business

Applications 1 2 5 8

Computerized

Accounting I 2 2

Concert Band I 3* 3

Concert Band II 2 2

Concert Band III 1 1



Concur Virtual Public

Speaking 1 1

Concurrent College

Algebra 1 1

Concurrent English

Comp II 4 3 1 4 1 13

Concurrent Finite

Math 2 2

Concurrent Virtual

Art Appreciation 1 1

80

Table 4.13 (Cont.)


Subject Matter

Concurrent Virtual

Eng Comp I 1 1

Concurrent Virtual

Eng Comp II 1 1

Concurrent Virtual

Gen Psychol 1 1

Concurrent Virtual

Hist Am Peo 1877-pr 1 1 2

Concurrent Virtual

Medical Terminology 1 1

Costume Design &

Construction 1 1

Creative Writing II 1 1

Credit Recovery 4 5 6 3 2 6 4 5 35

Criminology 1 1

Critical Reading 1 3 4

Critical Reading ESL 4 6 3 13

Critical Reading I 1 1

Critical Reading II 2 3 5

Cross Country 2 2

Cross Country Men 9 1 1

Cultural Studies 6 2 3 5 16

Customer Relations 1 1

Dance JV 2 2

Dawg Crew Service

Learning 3* 3

Debate I 4 6 1 4 15

81

Table 4.13 (Cont.)


Subject Matter

Debate II 2 2

Digital Learning 4 8 12

Drawing I 5 5 7 13 30

E.A.S.T. I 2 5 13 20

E.A.S.T. II 2 2

E.A.S.T. III 2 2

Early Childhood

Education 1 1

Economics 6 11 7 9 6 11 3 53

ELD 1 2 2

ELD 2 9/10 1 1

ELD 3 1 1

English 2 6 6 6 20

English 5* 5

English 10 18 11 14 4 10 7 8 15 11 98

English 11 10 10 10 8 11 9 2 14 74

English 12 4 4 6 8 8 8 12 11 61

English 9 3 3 3 6 15

English Alternate

Assessment 2 1 3

Environmental

Science 3 3 5 3 5 1 20

ESL Biology 1 1

82

Table 4.13 (Cont.)


Subject Matter

ESL English 10 1 1

ESL English 12 1 1

ESL English 9 1 1

Fashion

Merchandising 4 6 10

FHS Ambassador

Service Learn 4* 4

Financial Literacy 6 3 2 5 16

Food Safety &

Nutrition 10 9 17 7 8 12 63

Football 10* 10

Football 9 4* 4

Forensic Science 1 1 1

Forensics I 2 2 4

Forensics II 1 1

Foundations of

Health Care 3 5 3 1 12

French I 4 5 5 14

French II 1 2 7 10

Fund Audio Visual

Tech/Film 2 3 5

Fundamentals of

Television 4 5 9

Fundamentals

Photography 2 4 8 5 19

FYI Freshman Intro 1 2 3

Game Design

Programming II 3 2 5

83

Table 4.13 (Cont.)


Subject Matter

Geometry 23 8 14 13 2 9 69

Geometry 10 4 2 4 2 2 14

Geometry Part B 3 1 3 2 9

German I 9 6 15

German II 3 2 5

Golf 3* 3

Gothic Literature 1 1

Greenhouse

Management 3* 3

Health & Wellness 6 10 7 3 10 1 37

Housing Interior

Design 10 16 26


Independent Study 1 1 2


Tech/Film 2 2

Intermediate

Photography 1 1

Intermediate

Television 1 1 2


Design 4 4 7 15

JAG 5 2 7

JAG Apprenticeship 2 2

JAG I Apprenticeship 1 1 1 3

JAG II 4 4

84

Table 4.13 (Cont.)


Subject Matter

JAG II Work

Component 1 1

Journalism I 3 3 6

Journalism II

Newspaper 2 2

Journalism II

Yearbook 1 1 2

Journalism IV

Yearbook 1 1

Library Community

Service 1 1

Life Skills 5 3 2 10

Linear

Systems/Statistics 7* 7

Literary Magazine

I/Creative Writing 2 2

Literary Magazine III 1 1

Marketing 2 4 6

Math 5 2 4 6 17

Math 11 Alternate

Assessment 1 1

Media Comm A/V

Tech-Film Lab 1 1 2

Medical Terminology 3 6 9


Music Appreciation 8* 8

Native Spanish III 1 1

Nutrition & Wellness 1 1

Office Aide 3 1 1 5

85

Table 4.13 (Cont.)


Subject Matter

Oral Comm 9 9 18 9 6 6 7 18 82

Orchestra II 3* 3

Orchestra III 1 1

Orchestra IV 2 2

Orientation to

Teaching 2 2 4

Orientation to

Teaching II 3* 3

Outdoor Ed/Env

Science 9 5 3 17

Outdoor Education

PE 5 2 2 9

PE Aerobics/Cardio 3* 3

Personal Fitness For

Life 4 7 6 17

Physical Education 9 4 4 17

Physical Education

9th grade 10 5 8 14 17 54

Physical Education

Semester 4 6 8 18

Physical Science 18 15 17 14 8 22 94

Physical Science 9 6 3 4 5 18

Physics 11 10 6 1 28

Pre AP Algebra I 2 3 1 1 7

Pre AP Algebra II 3 3 7 1 5 1 4 4 28

Pre AP Biology 2 1 4 7

Pre AP Eng 10 1 1

86

Table 4.13 (Cont.)


Subject Matter

Pre AP English 10 6 6 5 5 4 1 8 35

Pre AP English 9 2 3 3 2 4 14

Pre AP French III 1 2 3

Pre AP German III 1 1

Pre AP Honors

Algebra I 1 1

Pre AP Physical

Science 5 3 8

Pre AP Spanish III 3 2 5 3 5 18

Pre AP Spanish IV 4 2 6

Pre AP Theatre 1 1

Pre AP World

History and Geog 2 2

Pre-AP Algebra I 1 10 20 7 5 17 10 70

PreAp Art I 8 4 12 24

Pre-AP Biology 7 16 2 17 15 15 4 11 87

Pre-AP Chemistry 4 3 4 2 1 2 3 19

Pre-AP English 9 2 15 20 11 1 12 16 77

PreAP French IV 3* 3

Pre-AP Geometry 6 4 4 5 3 1 2 25

Pre-AP Honors

Algebra I 4 5 1 10

Pre-AP Honors

Biology 3 10 1 6 6 6 32

Pre-AP Honors

English 9 2 7 7 4 3 5 28

87

Table 4.13 (Cont.)


Subject Matter

PreCalculus 4 5 4 2 4 2 21

Principles of Banking 2 2

Principles of

Engineering 3 3 6

Psychology 10 4 14

Quantitative Literacy 9* 9

Science 7 3 10

Small Business

Operations 5 4 9

Small Engine

Technology 5 5 10

Soccer Men 3* 3

Soccer Men 9 1 1

Soccer Women 3* 3

Social Studies 5 2 4 6 8 25

Sociology 4 3 6 13

Softball 2 2

Spanish for Native

Speakers I 2 4 6

Spanish I 4 3 10 8 9 10 44

Spanish II 1 6 5 2 3 3 1 2 23

Spanish Native

Speakers II 4* 4

Sports Med Injury

assessment 1 1

Sports Med Injury

assessment 3* 3

88

Table 4.13 (Cont.)


Subject Matter

Sports Medicine

Foundations 3 4 5 12

Stagecraft I 6 7 8 21

Stagecraft II 2 2

Street Law 9 9

String Orchestra I 6 6

Student Athlete

Leadership 2 2

Survey Agricultural

Systems 14 12 8 10 44

Symphonic Band I

(10) 1 1

Symphonic Band I

(9) 1 1

Symphonic Band II

(10) 1 1

Teacher Aide 2 6 5 1 6 3 13 6 9 51

Tennis Men 4* 4

Tennis Women 4* 4

Theatre Appreciation 20 10 30

Theatre I 2 2 4

Theatre II 3* 3

Theatre III 1 1


Track 18* 18

Track 9 3 2 5

89

Table 4.13 (Cont.)

Subject ZA 1st 2nd 3rd 4th ZB 5th 6th 8th

Total by

Subject

Matter


12 3 4 7

Transitional Math

Ready 3 6 9

US History 1 1 2

Veterinary Science 3* 3

Virt Careers in

Criminal Justi 1 1 2

Virt Digital Inform

Technology 1 1

Virt Intro Manu Prod

Des Innov 1 1

Virt Personal Fitness

for Life 3 2 1 1 1 8

Virt Sports & Entert

Marketing 1 1 1 2 1 6

Virtual AP

Psychology 1 1

Virtual Art in World

Cultures 1 1 1 2 1 1 7

Virtual Astronomy 1 1 1 1 4

Virtual Chinese I 1 1

Virtual Civics 1 4 2 1 3 3 14

Virtual Criminology 2 1 3 1 2 1 2 12

Virtual Digital

Photography I 1 1 1 3

Virtual Digital

Photography II 1 1 2

Virtual DR Found of

Personal Finance 2 1 1 4

Virtual Early

Childhood Educat 1 1 2

Virtual Earth Space

Science 1 1 2

90

Table 4.13 (Cont.)


Total by

Subject

Matter

Virtual Economics 5 2 1 2 7 3 1 3 24

Virtual

Entrepreneurship 1 1 2

Virtual Fashion &

Interior Des 2 2 1 2 3 10

Virtual Forensic

Science I 1 1

Virtual Forensic

Science II 1 1 1 3

Virtual French I 1 1

Virtual Gothic

Literature 1 1 1 1 4

Virtual Health &

Wellness 2 1 1 3 1 1 1 1 11

Virtual Health

Sciences 1 1 2

Virtual History of

Holocaust 1 2 3

Virtual Hospitality &

Tourism 1 1

Virtual International

Business 1 1 1 1 4

Virtual Latin 1 1 1 3

Virtual Latin II 1 1 2

Virtual Law and

Order 1 1 1 1 2 6

Virtual Marine

Science 1 1 1 2 1 1 7

Virtual Music

Appreciation 2 2 4

Virtual Mythology &

Folklore 1 3 1 5

Virtual Oral

Communications 2 1 1 3 6 3 6 4 5 31

Virtual Philosophy 1 2 1 4

91

Table 4.13 (Cont.)


Total by

Subject

Matter

Virtual Psychology 1 1 1 3 1 7

Virtual Social Media 1 2 3 2 1 9

Virtual Sociology I 1 1 4 1 7

Virtual Sociology II 1 1

Virtual Spanish I 2 2

Virtual Spanish II 1 1

Virtual Think &

Learn Strategies 1 1

Virtual Veterinary

Science 1 1 1 1 1 5

Visual Art

Appreciation 11 12 23

Vocal Music JV

Women 9 10* 10

Vocal Music Varsity

Men 9 4* 4

Vocal Music Varsity

Women 9 3* 3

Volleyball 6* 6

Wind Ensemble Band

III 1 1

Wind Ensemble Band

IV 1 1

Winter Guard 1 1



World Geography 4* 4

World History 6 6 17 9 4 9 7 6 64

92

Table 4.13 (Cont.)


Total by

Subject

Matter

Wrestling 9* 9

Total 170 428 465 496 477 162 429 459 478 3,564




Tables 4.11, 4.12, and 4.13 presented information on all classes and periods for chronically

absent students. The information was divided into categories and presented in the upcoming

tables which allowed departmental comparisons. The departments were Mathematics, English

Language Arts (ELA), Science, Social Studies, Career Technical Education (CTE), Fine Arts,

Non-Credit Classes, Health/Physical Education (PE), and World Languages. By dividing the

classes into these categories, the information for chronically absent students was disaggregated

into core classes, elective classes, and non-credit classes. Table 4.14 provides information on the

2016-2017 school year in these class categories. Mathematic classes represented 15.1% of the

classes taken in the 2016-2017 school year. Nearly 14% of students who were chronically absent

were absent from a mathematics class. Of the 743 students who were enrolled in a non-credit

class, 115 of them were chronically absent or 15.5%. The non-credit classes made up 4.3% of

the total classes enrolled by students, and 4.8% of the chronically absent student population.

93

Table 4.14

Chronically Absent Students by Departments for 2016-2017 School Year

Department CA Total Seats

in Dept

Percent

CA/Total

Taken

CA/Total

CA

Dept

Taken/

Dept Total

CTE 339 2,310 14.7% 14.2% 13.3%

ELA 372 2,598 14.3% 15.6% 14.9%

Fine Arts 274 1,797 15.2% 11.5% 10.3%

Health/PE 201 1,588 12.7% 8.4% 9.1%

Math 328 2,633 12.5% 13.8% 15.1%

Non Credit 115 743 15.5% 4.8% 4.3%

Science 280 2,257 12.4% 11.8% 13.0%

Social Studies 369 2,381 15.5% 15.5% 13.7%

World Languages 103 1,110 9.3% 4.3% 6.4%

During the 2017-2018 school year, the chronically absent student’s information by departments

is presented in Table 4.15. English Language Arts (ELA) represented 14.7% of the total classes

students were enrolled during the school year, and 15.5% of the chronically absent students.

Non-credit classes represented 3.7% of the total student enrollment, and 5% of the chronically

absent student enrollment. Therefore, slightly over one in five students in a non-credit course

were chronically absent from their non-credit class.

Table 4.15

Chronically Absent students by departments for 2017-2018 school year

Department CA

Total

Seats in

Dept

Percent

CA/Total

Taken

CA/Total

CA

Dept Taken/

Dept Total

CTE 391 2,384 16.4% 14.5% 14.1%

ELA 417 2,491 16.7% 15.5% 14.7%

94

Table 4.15 (Cont.)

Department CA

Total

Seats in

Dept

Percent

CA/Total

Taken

CA/Total

CA

Dept Taken/

Dept Total

Fine Arts 355 1,971 18.0% 13.2% 11.7%

Health/PE 255 1,554 16.4% 9.5% 9.2%

Math 372 2,494 14.9% 13.8% 14.7%

Non Credit 134 633 21.2% 5.0% 3.7%

Science 309 2,231 13.9% 11.5% 13.2%

Social Studies 348 2,157 16.1% 12.9% 12.8%

World Languages 114 994 11.5% 4.2% 5.9%

In Table 4.16, Fine Arts classes accounted for 10.9% of the total class enrollment for the 2018-

2019 school year. Of the chronically absent students, 13% of these students were enrolled in a

Fine Arts class. Of the 1,837 total Fine Arts enrollment, 462 students were chronically absent,

which represents 25% of the department seats in the 2018-2019 school year.

Table 4.16

Chronically Absent Students by Departments for 2018-2019 School Year

Department CA Total seats

in Dept

Percent

CA/Total

Taken

CA/total

CA

Dept

Taken/

Dept Total

CTE 554 2,397 23.1% 15.6% 14.3%

ELA 532 2,523 21.1% 15.0% 15.0%

Fine Arts 462 1,837 25.1% 13.0% 10.9%

Health/PE 291 1,463 19.9% 8.2% 8.7%

Math 500 2,520 19.8% 14.1% 15.0%

95

Table 4.16 (Cont.)

Department CA

Total

Seats in

Dept

Percent

CA/Total

Taken

CA/Total

CA

Dept Taken/

Dept Total

Non-Credit 117 589 19.9% 3.3% 3.5%

Science 448 2,115 21.2% 12.6% 12.6%

Social Studies 483 2,321 20.8% 13.6% 13.8%

World Languages 167 1,047 16.0% 4.7% 6.2%

Some students may be chronically absent from one or more classes. Each student in the dataset

was enrolled in 7 classes during the three school years, unless their 504 or IEP determined they

needed a shortened schedule. Table 4.17 provides information on how many classes the students

were chronically absent. In 2016-2017, 210 of the chronically absent students were only

chronically absent for one class period, which represented 28% of the total number. In 2018-

2019, 153 students were chronically absent from all seven of their classes.

Table 4.17

Breakdown of Number of Classes Chronically Absent Students Were Considered Chronically

Absent

2016-2017 2017-2018 2018-2019

Number of

Classes CA

Number of

students CA

% of

students

CA by

number

of

classes

Number

of

students

CA

% of

students

CA by

number

of

classes

Number

of

students

CA

% of

students

CA by

number

of

classes

1 210 28.0% 265 31.1% 285 27.4%

2 148 19.7% 147 17.3% 170 16.3%

3 107 14.2% 109 12.8% 136 13.1%

4 78 10.4% 89 10.5% 116 11.1%

96

Table 4.17 (Cont.)

Number of

Classes CA

Number of

students CA

% of

students

CA by

number

of

classes

Number

of

students

CA

% of

students

CA by

number

of

classes

Number

of

students

CA

% of

students

CA by

number

of

classes

5 68 9.1% 74 8.7% 95 9.1%

6 63 8.4% 67 7.9% 87 8.3%

7 77 10.3% 100 11.8% 153 14.7%

Table 4.18 presents the demographic information on race as compared to the number of classes a

student is chronically absent. Table 4.18 provides a comparison by race of students who were

chronically absent in one class compared to students who were chronically absent in all seven

classes. African-American students who were chronically absent from one class compared to

African-American students who were chronically absent from all classes had the largest change

in the three school years. In 2016-2017, 8.6% African-American students were chronically

absent from one class. When looking at students chronically absent in all classes, this percentage

increased to 19.5%. In 2017-2018, 8.3% of African-American students were chronically absent

from one class, then increased to 15.8% chronically absent from all classes. In 2018-2019,

African-American students who were chronically absent from one class was 6.3%. This

increased by over 250% to 16.3% for students chronically absent in all classes.

97

Table 4.18

Students who were chronically absent from one class compared to students chronically absent from all classes by race

2016-2017 2017-2018 2018-2019

One

CA

class %

Seven

CA

classes %

One

CA

class %

Seven

CA

classes %

One

CA

class %

Seven

CA

classes %

Asian 9 4.3% 2 2.6% 5 1.9% 4 4.0% 10 3.5% 2 1.3%

Black 18 8.6% 15 19.5% 22 8.3% 16 15.8% 18 6.3% 25 16.3%

Hawaii/

Pacific

Islander

2 1.0% 1 1.3% 2 0.8% 2 2.0% 0 0.0% 1 0.7%

Hispanic or

Latino 23 11.0% 11 14.3% 36 13.6% 13 12.9% 29 10.2% 29 19.0%

Native

American/

Alaskan

Native

0 0.0% 0 0.0% 1 0.4% 0 0.0% 0 0.0% 1 0.7%

Two or More

Races 16 7.6% 2 2.6% 9 3.4% 2 2.0% 21 7.4% 12 7.8%

White 142 67.6% 46 59.7% 190 71.7% 64 63.4% 207 72.6% 83 54.2%

98

Table 4.19 presents the number of chronically absent classes of special education students during

2016-2017, 2017-2018, 2018-2019 school years. In 2017-2018, 22.8% of SPED students were

chronically absent from all seven classes. In 2018-2019, 23.6% of chronically absent SPED

students were chronically absent from all seven classes.

Table 4.19

Comparison of Special Education chronically absent students to chronically absent total

population by classes

2016-2017 2017-2018 2018-2019

Number

of

Classes

CA

Total CA

population

SPED CA

Population

Total CA

population

SPED CA

Population

Total CA

population

SPED CA

Population

1 28.0% 22.8% 31.1% 15.7% 27.4% 18.4%

2 19.7% 17.5% 17.3% 11.8% 16.3% 8.0%

3 14.2% 5.3% 12.8% 11.8% 13.1% 14.4%

4 10.4% 14.0% 10.5% 14.2% 11.1% 9.2%

5 9.1% 12.3% 8.7% 14.2% 9.1% 14.4%

6 8.4% 15.8% 7.9% 9.4% 8.3% 12.1%

7 10.3% 12.3% 11.8% 22.8% 14.7% 23.6%

Table 4.20 presents the students who were chronically absent for all seven classes by

grade level. Of the ninth-grade students who were chronically absent, 19.8% of them were

chronically absent from all seven classes in the 2018-2019 school year. During the 2018-2019

school year, the chronic absences for ninth grade students increased from 26% to 44% in one

school year.

Table 4.20

Students chronically absent from all class periods by grade level

Grade 2016-2017 2017-2018 2018-2019

9th grade 7.6% 10.7% 19.8%

10th grade 10.9% 11.7% 16.7%

11th grade 10.4% 11.5% 9.5%

12th grade 10.9% 12.2% 9.7%

99

CHAPTER FIVE: ANALYSIS, IMPLICATIONS AND RECOMMENDATIONS

Introduction

The purpose of this study was to provide insight and understanding of the chronically

absent students and their common characteristics at High School X. This chapter was designed

to provide discussion, recommendations, and conclusions (Lunenburg & Irby, 2008) from the

data presented in Chapter Four. The dataset included archival data from the 2016-2017, 2017-

2018, and 2018-2019 school years at High School X. The dataset included information on

absenteeism, demographic information such as ethnicity, grade level, SPED and ELL status,

lunch status, detailed information on the type of class, and time of day and the class the absence

occurred. The organization of Chapter Five is centered around the two research questions

analyzed in this research study: (1) What correlation, if any, does demographic information have

with students’ chronic absenteeism at High School X? (2) What are the correlations, if any,

among students’ chronic absenteeism and the class period of the absence?

The research method used was a non-experimental, correlational quantitative research

study. The quantitative data was obtained by analyzing archival data in the Arkansas state

reporting systems, Cognos and E-School. The data was gathered through a series of reports from

these two systems. The data reports first run was used to identify the students who were

chronically absent. The second phase of reports were run for demographic information on the

chronically absent students. The third phase of reports included information on the classes that

the identified chronically absent students missed most often. After identifying information for

the chronically absent students, the reports were created to determine the demographic and class

information of the total student population. Next, the demographic information was compiled

into large spreadsheets which were used to create the tables found in Chapter Four.

100

Chapter Five includes a quantitative analysis on each of the research questions. The

analysis includes combining information found at High School X to the information presented in

Chapter Two discussing absenteeism trends happening in schools across the United States. This

chapter revisits the limitations and delimitations on this topic, and the recommendations for

future research.

Research Question One

What correlation, if any, does demographic information have with students’ chronic


The data from the 2016-2017, 2017-2018, and 2018-2019 school years was broken down

into subcategories based on demographic information. This demographic information included

race/ethnicity, grade level, SPED and ELL status, and free or reduced lunch status. This

demographic information was compared to the demographic information found in the review of

literature articles for national or other state standards in the writing of this chapter.

Race/Ethnicity. According to the United States Department of Education (2016), “Black

students represent 16% of all students, but 21% of chronically absent students” (p. 8). At High

School X, this data was different and not consistent with previous research studies. Only during

2018-2019 school year, there was a percentage of Black students, who were chronically absent

more than the percentage of Black students represented in the total population. The percentage

was only 0.5% higher, as Black students represented 10.2% of the total student population and

10.7% of the chronically absent population. During the other three school years, the percentages

were lower for Black students. At High School X in the race/ethnicity category, the percentages

of chronically absent students by race were close to the percentage of the subcategory in terms of

the total population during the three identified school years. The only subcategory that showed a

101

higher percentage of chronically absent students over the percentage in the total population was

the two or more mixed-race category during the three school years. During the 2016-2017

school year, two or more races represented 3.2% of the total population and 4.4% of the

chronically absent population. In 2017-2018, two or more races was 3.9% of total population

and 4.4% of chronically absent population. In 2018-2019, two or more races represented 5.0%

of total population and 5.9% of the chronically absent population.

By looking more in depth at race, 23% of Black students, 20% of Native American, 21%

of two or more, and 21% of Latino students were chronically absent according to the U.S.

Department of Education (2016). At High School X, these percentages were both similar and

different, and varied by school year. During the 2016-2017 school year, Black (25%) students,

Native Indian (20%) students, White (26%) students, two or more races (36%) students, and

Latino (28%) students were absent. In the 2017-2018 school year, Black (31%) students, Native

Indian (15%) students, White (34%) students, two or more races (38%) students, and Latino

(35%) students were chronically absent. During the 2018-2019 school year, each of these

percentages increased except the Native Indian race. Black students (44%), White students

(42%), Latino students (41%), and two or more races (50%) were chronically absent.

Demographic information, specifically race/ethnicity percentages in the Black category

dramatically changes when delving into the comparison by number of classes chronically absent.

African-American students account for 8.6% of the students who are chronically absent from

only one of their seven classes in the 2016-2017 school year. This jumps to 19.5% when

focusing on students who were chronically absent from all seven classes. In the 2017-2018

school year, African-American students went from being 8.3% chronically absent from one class

to being 15.8% chronically absent from all seven classes. In the 2018-2019 school year, African-

102

American students accounted for 6.3% of the students being chronically absent from one class,

and being 16.3% chronically absent from all seven classes. The Hispanic/Latino sub-category

also had some shifts, but not to the degree of the African-American group. In the 2016-2017

school year, the Hispanic/Latino group went from 11% being chronically absent from one class

to 14.3% being chronically absent in all seven classes. In the 2017-2018 school year, this

percentage dropped to 12.9%. In the 2018-2019 school year, the percentage for the

Hispanic/Latino subcategory was 10.2% being chronically absent from one class and increased

to 19% chronically absent from all seven classes.

Grade Level. “Empirical studies examining truancy characteristics based on age reveal

that as student age increased, there is a concurrent increase in student school avoidance behavior,

with upper grades in high school exhibiting the highest rates of truancy” (Jones et al., 2011, p. 9).

The four grade levels over the three school years demonstrated this pattern until the 2018-2019

school year. During the 2016-2017 school year, the ninth grade represented 26% of the total

student population, and 17% of the chronically absent population. Tenth grade students were

25% of the total student body, and 21% of the chronically absent population. The eleventh grade

students were 25% of total student population, and 29% of the chronically absent population.

The twelfth grade students followed the national trend by representing 24% of the total student

population, and 33% of the students who were chronically absent. The 2017-2018 school year

followed the national trends; however, the 2018-2019 school year presented different

information. During the 2018-2019 school year, ninth grade students represented 24% of the

total student population, and 29% of the chronically absent population. Tenth grade students

were 27% of the population, and 26% of the chronically absent. Eleventh grade students were

25% of total student population, and 21% of the chronically absent. The twelfth-grade students

103

represented 24% of the total student population, and 24% of the chronically absent students. In

ninth grade class, 44% of the students were considered chronically absent, which contrasts to the

twelfth-grade class where 36% of them were chronically absent. “Chronic absenteeism begins to

rise in middle school and continues climbing through twelfth grade, with seniors often having the

highest rate of all” (Balfanz & Byrnes, 2012, p. 5).

English Language Learner, Special Education and Lunch Status. During the 2016-

2017 and 2018-2019 school years, the special education students at High School X had lower

numbers of chronically absent students as compared to the national averages. In the 2016-2017

school year, special education students were 12% of the total student population, and only 8% of

the chronically absent student population. During the 2018-2019 school year, special education

students were 11% of the total population, and 17% of the chronically absent population.

However, the 2017-2018 school year was different from the 2016-2017 and 2018-2019 school

years. Special education students represented 10% of the total student population, and 14% of

the chronically absent population. When you look at the sub-category of special education

individually, in the 2017-2018 school year, 41% of the special education students were

chronically absent and in 2018-2019, 54% of special education students were chronically absent.

These percent were very different from the 2016-2017 school year when only 17% of special

education students were chronically absent.

During the three school years, the English Language Learner student population was

fairly similar each year. During the 2016-2017 school year, ELL students made up 8% of the

total population, and 10% of the chronically absent population. In the 2017-2018 school year,

these students were 6% of the total population, and 8% of the chronically absent. During the

2018-2019 school year, these students were 6% of total population, and 7% of the chronically

104

absent population. While these numbers do not appear to be drastically different each year;

however, by only focusing on the ELL population, a slightly different picture may become

clearer. Of the ELL population, 32% (2016-2017), 38% (2017-2018,) and 42% (2018-2019)

were chronically absent during the researched school years.

Students who qualify for free or reduced lunches represented the largest differences

among chronically absent students during two school years. In 2017-2018, 28% of the total

student population were on the free or reduced lunch status, and yet they made up 34% of the

chronically absent population. During the 2018-2019 school year, these students represented

35% of the total student population and 39% of the chronically absent population. In the 2018-

2019 school year, 40% of the free or reduced lunch students were considered chronically absent.

This number was higher as compared to the previous two school years, as 36% of students were

chronically absent in the 2017-2018 school year and 26% were chronically absent in the 2016-

2017 school year.

The number of students who were received both special education services and qualified

for free/reduced lunch status presented a different picture in terms of chronically absent students.

Over 60% of students who were identified in both subcategories were chronically absent. In

2018-2019, 54% of the students who qualified for special education and free/reduced lunch

status were chronically absent from five or more classes. This is very different from the total

chronically absent population with only 32% of the chronically absent population being absent

from five or more classes in the same school year.

Research Question Two

What are the correlations, if any, among students’ chronic absenteeism and the class

period of the absence?

105

The U.S. Department of Education (2016) released information and found “…19% of all

high school students are chronically absent. Chronic absenteeism was defined at missing more

than 10% of the school days, for any reason” (London et al., 2016, p. 4). Chronic absenteeism is

being counted as a full day absence. At the high school level, partial day absences are a more

significant issue. At High School X, a full day chronic absence would be demonstrated by

students who have missed six or seven of their classes. The rates of a full day absence during the

three school years studied were 18.7% (2016-2017), 19.7% (2017-2018), and 23% (2018-2019).

By taking a closer look and observing each class individually at High School X, the chronically

absent rates were 28% (2016-2017), 34% (2017-2018), and 42% (2018-2019), which represented

a much higher rate than the national average. These high percentages demonstrate the need to

review the material on chronic absenteeism in individual classes for high school students. For

this research study, all information was based on an individual class, not a full day absence.

Research Question Two focused on two distinct pieces of information. The first piece of

information was the time of day of a class. This information focused on the period of day the

chronic absenteeism had occurred. At High School X, the schedule was setup on a block

schedule where students enrolled in seven classes and had an advisory period. The advisory

period was not analyzed in this research study as only academic classes in a student’s schedule

were included in this data analysis. Students took four blocks on an A-Day, and three blocks

along with the advisory period on a B-Day. A student’s schedule had seven academic periods

unless a 504 or IEP plan reduced their schedule. Both A-Day and B-Day had a Zero-Hour class.

A Zero-Hour class started at 7:15 am and students who were enrolled in a Zero-Hour class ended

their school day at 2:15 pm. If a student was not enrolled in a Zero-Hour class, their day started

106

at 8:50 am and ended at 3:50 pm. Each day, there were three lunch periods, and these lunches

were included in the second hour and sixth hour block in a student’s schedule.

The second piece of information focused on the type of class the student was enrolled in

during that schedule block. This research focused on the class subject matter including

Mathematics, Science, English (Core class), classes such as World Languages or Career

Technical Classes (elective class), or classes such as Teacher’s aide, Office aide, or Credit

Recovery (non-credit classes). Students enrolled in non-credit classes did not receive a grade in

the non-credit classes. The data collected on subject matter focused on individual classes and

divided the individual classes into departments.

Time of Day. During the 2016-2017 school year, Zero-Hour was the block period that

had the most chronically absent students. “Relative to later periods of the day, classes that meet

in first period are associated with higher rates of absenteeism” (Cortes et al., 2012, p. 1). Zero-A

block had absent rate of 19.7%, and Zero-B Black had an absent rate of 19.1%. Twenty percent

of the total student population in Zero-A were considered chronically absent during the 2016-

2017 school year. The next class periods that students who were chronically absent were the end

of the day periods, fourth period at 17.6% and eighth period at 17.5%. The other class periods

had between 11 and 12% chronic absenteeism.

In the 2017-2018 school year, Zero-A and Zero-B periods still had the highest percentage

of chronically absent students. Zero-A block had 22.5% chronic absenteeism, and Zero-B block

had 23.1% chronic absenteeism. Again, the next highest class periods with chronic absenteeism

were at the end of the day with fourth period having 19.5% and eighth period having 19.4%.

There was an increase in the percentage of third and sixth periods having between 15-16%

chronic absenteeism.

107

The 2018-2019 school year indicated a significant increase in the percentage of

chronically absent students in each class period. During Zero-A, chronically absent students rose

to 26.1% and Zero-B was 27.6%. The last periods of the day also increased in the percentage of

students being chronically absent. During fourth period, it was 27.2% and eighth period was

26.2%. This was the first time the Zero-Hour blocks were not the highest percentage during the

three-year period. The percentage of chronically absent students in first and fifth hours increased

to 17.6% and 17.7%, while second and sixth hours (the blocks with lunches) rose to 19.2%. The

increases in chronic absenteeism for the 2018-2019 school year could be attributed to the change

in priority for administrators. The priority in the 2018-2019 school year was graduation rates

and not attendance rates.

Subject Matter. The subject matter data provided insight into the chronically absent

students. For the 2016-2017 and 2017-2018 school years, the class with the highest number of

students who were chronically absent was English 12. English 12 represents a core class, which

is a class students must have to graduate high school. English 12 is the fourth English class a

student would take while a high school student. When the single-subject matter courses were

divided into departments, the data provided more insight into the chronically absent student at

High School X. Non-credit classes accounted for 4.3% of the total classes enrolled by the total

student population, and 4.8% of the chronically absent population were enrolled in non-credit

classes. During the 2016-2017 school year, 15.5% of the students were chronically absent from

their non-credit classes. Also, in the 2016-2017 school, the social studies department

experienced 15.5% of their students were chronically absent from classes. Social Studies classes

represented 13.7% of the total classes the total student body was enrolled, and 15.5% of the

chronically absent population. Surprisingly, only 9% of the total students enrolled in World

108

Languages were chronically absent from these classes. Ironically, World Language is not a

requirement for graduation at High School X; therefore, the students who enrolled in these

courses chose to do so, as they are not required for graduation.

During the 2017-2018 school year, non-credit classes had the highest percentage of

chronic absenteeism. During this school year, 21.2% of the students enrolled in a non-credit

class were chronically absent from this type of class. Non-credit classes accounted for 3.7% of

the total class enrollment, and 5% of the total percentage of chronically absent students. The

next department with the highest percentage of chronically absent students was the Fine Arts

department. Eighteen percent of the students who enrolled in a Fine Arts type courses were

chronically absent. During this school year, World Languages accounted for the lowest

percentage of chronic absenteeism with only 11.5% of the total students enrolled in a World

Language class being chronically absent.

During the 2018-2019 school year, Fine Arts had the highest percentage of chronically

absent students. Of the students enrolled in a Fine Art class, 25% were chronically absent from

their Fine Arts class. Fine Arts classes accounted for 10.9% of the total class enrollment, and

13% of the chronically absent enrollment population. Again, World Languages had the lowest

percentage of chronically absent students with 16%. During the 2018-2019 school year, non-

credit classes were low with only 3.3% students being chronically absent in these courses.

Outliers. In Chapter Four, Tables 4.11, 4.12, and 4.13 identified some outliers in the

data. These outliers represented chronic absences that did not follow the data trends that

occurred in the bookends of the day including Zero-Hours and last periods, which were possibly

30% higher than the other chronic absences presented in the tables. These outliers fell into

different categories including occurrences during lunches, occurrences at the beginning of a

109

school day, being singlet classes (only offered once in the master schedule), or an outlier that did

not have a specific reason. The classes identified with an asterisk represented classes that were

only offered once in the master schedule and had three or more chronic absences.

In the 2016-2017 school year, Football/Freshman represented one of the identified

individual outliers as it was only offered during first period, and had six students who were

chronically absent. Freshman football was also considered an outlier because it did not follow

the data trends presented in Chapter Four. This class only had ninth grade students enrolled,

which represented the lowest grade level with chronically absent students in the 2016-2017

school year. Due to this class only being offered one period in the master school schedule, the

researcher was unable to determine if this was an outlier, or would other similar subject class

periods follow the same data trend.

Another identified course outlier was Health in the 2018-2019 school year. During that

school year, the number of chronic absences in Health had the highest numbers in second and

sixth periods, which did not follow the trend data. Health classes were mainly freshman level

classes, with second and sixth periods falling in the middle of the school day. In addition,

second and sixth period classes were during the three lunch periods of the school day. Students

may have gone to all three lunch periods to socialize with friends and others rather than attending

class, which may have accounted for higher absences.

In the 2018-2019 school year, Geometry could also fall into an outlier category.

Geometry is primarily a tenth-grade class with the highest percentage of chronic absences during

in second period. With Geometry being a tenth-grade class and falling in the middle of the day,

it also does not follow the data trend. Similar to the Health class previously discussed, this was

also a class period where all three lunches fell, and students would be able to socialize with all

110

their friends during this time. Many of the outliers identified in Tables 4.11, 4.12, and 4.13 from

Chapter Four fall into this same situation and overall conclusion. The highest number of chronic

absences by class occurred during the lunch periods, which offers an explanation to these higher

numbers in the data analysis.

During the 2016-2017 school year, AP Language and Composition was another identified

outlier. This course had thirteen students who were chronically absent from their first period

class. AP Language and Composition was an eleventh-grade class. This outlier could be

explained by the class being offered during the first period of the day. This class was not a Zero-

Hour class, but not all students enrolled in Zero-Hour. Therefore, first period would represent

the beginning of their school day, which followed the national trend of students missing the first

class period of the day.

During the 2018-2019 school year, there was an outlier that could not be explained with

other reasons. One course of World History had 17 students who were chronically absent during

third period, which almost doubled the number of chronic absences as compared to other World

History sections. World History was a course credit required for graduation. Eleventh-grade

students primarily enrolled in the course, which falls in the middle of the day. Based on trends

and previous research, there is not proven data to explain why this class had such higher chronic

absences among their enrolled students. Of the three school years of trend data, this type of

outlier very rarely occurred.

Implications

Demographics

The implications of this research study on the chronic absenteeism demographics at High

School X provided important findings for future research. The research showed that students

111

who qualify for free or reduced lunches accounted for the highest percentage of chronic

absenteeism at High School X. By using this knowledge, it could help shape ways to reach these

students and their families on how to connect to their high school classes. The data provided

another implication based on the grade levels. The data from the twelfth graders was consistent

with data from previous studies. This finding implies the need to have classes that keep twelfth

grade students engaged and motivates them to finish the school year. Another possibility might

be reducing the number of classes that are required by twelfth grade students to only classes that

are required for graduation. The demographic information also has an implication on policy

making at the district level, the district policy would need to evaluate ways to decrease chronic

absenteeism within the entire school district. “School attendance policies should ideally set clear

expectations, be aligned with overall district policies, and promote the understanding among all

school community members, including parents” (Hanover Research, 2016, p. 14).

Socialization theory is the understanding of societal attitudes. The society attitudes at

the high school level can be demonstrated by the attendance expectations of a school district

and state laws concerning attendance. In the 2016-2017 and 2017-2018 school years,

attendance was a priority category for administrators to focus on for their students.

Administrators made phone calls to parents and pulled students in to discuss where they were

at in their attendance for their classes. In the 2018-2019 school year, graduation rates became

the focus and priority for administrators. In the school year, where the focus shifted, chronic

absenteeism increased by 8%. When the school’s expectations of attendance and attendance

policy shifted, so did the student’s shift on the importance of attendance; thus, reinforcing the

Socialization theory. By partnering with parents, the school can look for ways to improve

attendance in students, which reinforces the primary tenets of Socialization theory. This is

112

particularly true when students as children begin to frame their own understanding based on

the beliefs and habits of those around them, which can come from parents, peers, and school

expectations.

Class Period. The implications of a class period including the subject and department of

the class and the time of day of the class, it leans towards influencing the practitioners at a

school. The school staff including teachers and administrators can analyze the class period data

for chronic absenteeism and begin discussing different options of when classes should be offered

certain times of the day, or ways to improve attendance during the Zero-Hour or the last hour of

the day. As previously discussed, Zero-Hour and the last hour of the day have the highest

percentage of student chronic absenteeism.

Another implication from the data was provided by the English 12 class information.

During the 2016-2017 and 2017-2018 school years, English 12 represented the highest number

of chronic absences. In the 2018-2019 school year, it did not have the highest number of chronic

absences, one reason could be because it was not offered during eighth period. Teachers and

Administration can also “…partner with parents, parental attendance awareness and support

programs have potential to be powerful, and schools can leverage this partnership in numerous

ways to address absenteeism” (Gottfried & Hunt, 2019a, p. 8).

According to Bandura (1971), Social Learning Theory stated, “…virtually all learning

phenomena resulting from direct experiences can occur on a vicarious basis through

observation of other people’s behavior and its consequences for them” (p. 2) . Based on this

theory, there is an understanding that students will learn from what happens to those closest

around them. Unfortunately, many underclassmen could be learning and imitating the chronic

absenteeism behaviors of their upperclassmen, as well as other factors, such as the ability to

113

drive and leave campus on their own. In the 2016-2017 school year, 18% of ninth grade

students were chronically absent. In the 2017-2018 school year, the tenth-grad cohort grew to

29% of them being chronically absent. In the 2018-2019 school year, the eleventh grade class

increased to 31% being chronically absent. The increases of chronic absenteeism for this

cohort group demonstrates one tie to the Social Learning Theory. Students learned this

behavior, whether it was positive or negative behavior by observing the behavior of their

peers and seeing first-hand the consequences, or lack of consequences for that learned

behavior.

Recommendations

Based on the previous literature on chronic absenteeism and the current school systems,

the researcher has determined a few systemic recommendations. By creating an attendance

administrator or attendance team, it will make attendance a priority at school, which was a

proven result, in another school in the nation, towards decreasing chronic absenteeism. “From

1996 to 1997 as schools developed … partnerships to help improve school attendance, the

average rate of chronically absent students in the schools decreased from 8% to 6.1%” (Epstein

& Sheldon, 2002, p. 311). This attendance team would focus on everything related to student

attendance.

One of the attendance team objectives would be to increase the communication with

parents. A school district in Washington State had an improvement in attendance by 62% when

families received attendance letters (Lara et al., 2018). Epstein and Sheldon (2002) stated

students who received rewards for improving their attendance created a positive change in their

chronic absenteeism. The attendance team would include rewards as part of their attendance

114

program to decrease chronic absenteeism. These rewards could be in the form of dance tickets,

parking passes, athletic passes, or even changes to a student’s twelfth grade schedule.

Reid (2002) described schools in the United Kingdom that are providing alternative

programs where students in their last year of school are allowed to “…further education college,

gain experience on long-term work placement, or learn new skills with training organizations”

(Reid, 2002, p. 58). Further research must be conducted that focuses on the implications of

requiring students to enroll in a full class schedule, when not all classes are needed for

graduation requirements. For example, non-credit classes accounted for the most chronically

absent students during the 2016-2017 and 2017-2018 school years. During the 2016-2017, 2017-

2018, 2018-2019 school years, the senior class represented over 35% of the chronically absent

students. The classes with the highest chronic absenteeism were classes taken primarily by

seniors during the three researched school years. One recommendation is to find possible

alternatives for seniors during their last school year based on the chronic absenteeism problem

with these students. Possible alternatives could include an internship class, providing high

school credit for working with Jobs for Arkansas Graduates (JAG), or allowing students a

shortened school day. Birioukov (2016) provided research on the need for students to help

supplement family income, so students having opportunities to have a job, and receive high

school credit is a research supported solution. Another recommendation is “…develop a staff

capacity to engage in effective attendance practices through professional development and

coaching of teachers” (Bartanen, 2020, p.2).

In 2005, the Oakland Unified School District implemented a chronic absenteeism

initiative and within this initiative they provided teachers with a manual “…called “Every Day

Counts” to give staff clear guidance on how and when to address chronic absence” (Hanover

115

Research, 2016, p. 26). This initiative “…found that 19% of its schools had reduced their

chronic absence rate to 5% or less” (Hanover Research, 2016, p. 27). With this recommendation,

there is a need to review the change in the number of students who were chronically absent from

all seven classes. The number of ninth grade students chronically absent from all seven classes

jumped from 10.7% in 2017-2018 to 19.8% in 2018-2019. Within the High School X school

district, the priority shifted from attendance rates to graduation rates. Ninth grade students

would be a very low priority in focusing on graduation rates because they have four years to

complete their classes for graduation. However, if the focus is not on attendance, graduation

rates could be impacted in later years. According to Bridge et al. (2013), absenteeism is a sign of

a student who is going towards educational failure.

A further research recommendation would be weighing the positives and negatives of

including Zero-Hour in a block schedule. As previously discussed, Zero-Hour accounted for the

highest percentage of chronically absent students in all three researched school years. The data

analysis concluded that Zero-A and Zero-B classes accounted for the highest percentage of

chronic absenteeism in all three school years as demonstrated in Table 4.10 in Chapter 4. By

coupling the high school student Zero-Hour data with the early start time class data, it would

indicate one reason to not have Zero-Hour in a schedule for high school students. “… (L)ater

school starts may be an important tool for combating sleep loss and the negative outcomes

associated with sleep deprivation” (Marx et al., 2017, p. 10).

Further research is needed to address the rise in students from lower grade levels who are

missing all seven periods as demonstrated in Table 4.20 in Chapter 4. Was the student data of

students missing all seven periods an outlier, or did this trend continue after this school year?

This is an important question for the administration to assist in helping solve the chronic

116

absenteeism problem at High School X. The freshman class rise in chronic absenteeism must be

monitored. If the ninth-grade cohort continues to trend in high percentages of chronic

absenteeism, are the cohorts behind them learning from this behavior, or was this also an outlier?

To decrease the number of students who are chronically absent, administrators must make it a

priority and focus within the school for significant changes in student behavior to occur.

Reflection.

What happens now? I have learned a plethora of knowledge through this

research. I have started to understand the complexities of chronic absenteeism at High School X.

This research has provided a starting point for future discussions with school and district

administration. It has also given a new focus to me. Through this research, I now know the

demographics of the chronically absent student and what type of class they are absent from in

their schedule. My thought process has changed throughout the four years of this adventure.

When I first started, I was very black and white in my thinking – if students missed too many

days, then we need to deny credit based on attendance. As I have delved into this research and

read of the multitude of reasons why students are absent, I don’t want to deny them credit. I

want to provide the students with an awareness at the start of the semester and all throughout the

semester and prevent the absences from even happening in the first place. When I begin thinking

about what I can implement to start making changes to improve chronic absenteeism, the first

thought is awareness. If the school wants to improve, there needs to be an awareness of the

absences. My plan for awareness includes phone calls, letters and text messages with detailed

information on absences to both parents and students. The next level of awareness is to

implement an attendance team who can work with students and begin building relationships to

help the students feel welcome at the school.

117

References

Ahmad, F. A, & Miller, T. (2015). The high cost of truancy. Center for American Progress.

Allensworth, E. M., Gwynne, J. A., Moore, P. & Torre, M. (2014). Middle grade indicators of

readiness in Chicago public schools. The University of Chicago Consortium on Chicago

School Research.

Anderson, K., Egalite, A. J., & Mills, J. N. (2019). Absent from school. Cambridge,

Massachusetts: Harvard Education Press.

Arkansas Department of Education. (2018, January 30). Attendance.

https://dese.ade.arkansas.gov/Offices/learning-services/attendance

Balfanz, R. & Byrnes, V. (2012). The importance of being in school: A report on absenteeism in

the nation’s public schools. Education Digest, 78(2), 4-9.

Balfanz, R., Herzog, L. & Mac Iver, D. J. (2007). Preventing student disengagement and keeping

students on the graduation path in urban middle-grades schools: Early identification and

effective interventions. Educational Psychologist, 42(2), 223-235.

Baltimore City Health Department. (2009). Examination of youth violence in Baltimore city

2002-2007. Health Department, Baltimore Maryland. Retrieved from

https://www.baltimorehealth.org/wp-content/uploads/2016/06/Examination-of-Youth-

Violence-in-Baltimore-City-FINAL.pdf

Bandura, A. (1971). Social learning theory. General Learning Press.

Bartanen, B. (2020). Principal quality and student attendance. Educational Researcher.

Bauer, L., Liu, P., Schanzenbach, D. W., & Shamburgh, J. (2018). Reducing chronic absenteeism

under the every student succeeds act. Strategy Paper Hamilton Project.

Birioukov, A. (2016). Beyond the excused/unexcused absence binary: classifying absenteeism

through a voluntary/involuntary absence framework. Educational Review, 68(3), 340-

357.

Bloomberg, L. D., & Volpe, M. (2016). Completing your qualitative dissertation: A road map

from beginning to end. Thousand Oaks: Sage.

Bridge, B. J., Curtis, L. E., & Oakley, N. (2013). No single source, no simple solution: Why we

should broaden our perspective of the school-to-prison-pipeline and look to the court in

redirecting youth from it. Journal of Educational Controversy, 7(1).

Brown, B. B., Mounts, N., Lamborn, S. D., & Steinberg, L. (1993) Parenting practices and peer

group affiliation in adolescence. Child Development, 64, 467-482.

118

Chang, H. N., & Romero, M. (2008). Present, engaged, and accounted for: The critical

importance of addressing chronic absence in the early grades. National Center for

Children in Poverty. Executive summary report

Chang, H. N., Russell-Tucker, C., & Sullivan, K. (2016). Chronic early absence: What states can

do. Phi Delta Kappan, 98(2), 22-27.

Cortes, K. E., Bricker, J., & Rohlfs, C. (2012). The role of specific subjects in education

production functions: Evidence from morning classes in Chicago public high schools.

The B.E. Journal of Economic Analysis & Policy, 12(1).

Corville-Smith, J., Ryan, B. A., Adams, G. R., & Dalicandro, T. (1998). Distinguishing absentee

students from regular attenders: The combined influence of personal, family, and school

factors. Journal of Youth and Adolescence, 27(5), 629-640.

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods

approaches. Los Angeles, CA: SAGE.

Cronk, G. (1995). George Herbert Mead. The Internet Encyclopedia of Philosophy, ISSN 2161-

0002. Retrieved from https://www.iep.utm.edu/

Epstein, J. L., & Sheldon, S. B. (2002). Present and accounted for: Improving student attendance

through family and community involvement. The Journal of Educational Research,

95(5), 308-318.

García, E., & Weiss, E. (2018). Student absenteeism: Who misses school and how missing

school matters for performance. Economic Policy Institute.

Garin, G. (2012). Skipping to nowhere. Get Schooled, Hart Research.

Garry, E. (1996). Truancy: First step to a lifetime of problems. Department of Justice.

George W. Bush Institute. (2018). Spotlight: Chronic absenteeism.

Gilligan, C. (1982). In a different voice: Psychological theory and women’s development.

Cambridge, MA: Harvard University Press.

Ginsburg, A., Jordan, P., & Chang, H. (2014). Absences add up: How school attendance

influences student success. Attendance Works.

Gottfried, M. A., & Hutt, E. L. (2019a). Addressing absenteeism: Lessons for policy and

practice Policy Analysis for California Education, PACE.

Gottfried, M. A., & Hutt E. L. (2019b). Absent from School. Cambridge, Massachusetts: Harvard

Education Press.

119

Hanover Research. (2016, August). Best practices in improving student attendance. Hanover

Research, Arlington VA.

Hartnett, S. (2007). Does peer group identity influence absenteeism in high school students? The

High School Journal, 91(2) 35-44.

Jones, L., Finnegan, D., & Harris, R. (2002). The school attendance demonstration project.

Research on Social Work Practice, 12(2) 222-237

Jones, T., Lovrich, N., & Lovrich, N. (2011). Updated literature review on truancy: key

concepts, historical overview, and research relating to promising practices – with

particular utility to Washington State. Center for Children and Youth Justice.

Kohlberg, L. (1969). States in the development of moral thought and action. New York, NY:

Holt, Rinehart and Winston.

Lara, J., Noble, K., Pelika, S., Coons, A., & National, E. A. (2018). Chronic absenteeism. NEA

research brief. NBI no. 57. National Education Association.

Liu, J., & Loeb, S. (2016). Going to school is optional: Schools need to engage students to

increase their lifetime opportunities. Brookings.

Lochmiller, C. R. (2013). Improving student attendance in Indiana’s schools. Indiana

Department of Education.

London, R. A., Sanchez, M., & Castrechini, S. (2016). The dynamics of chronic absence and

student achievement. Education Policy Analysis Archives, 24(112).

Lunenburg, F. C., & Irby, B. J. (2008). Writing a successful thesis or dissertation. Corwin Press,

Thousand Oaks, CA.

Marx, R., Tanner-Smith, E. E., Davison, C. M., Ufholz, L., Freeman, J., Shankar, R., Newton, L.,

Brown, R. S., Parpia, A. S., Coxma, I., Hendrikx, S. (2017, December). Later school start

times for supporting the education, health, and well-being of high school students: A

systematic review. Campbell Systematic Reviews 2017:15.

Mertler, C. A. (2019). Introduction to Educational Research (2nd edition). Thousand Oaks,

California: Sage Publications.

Ravitch, S. M., & Riggan, M. (2017). Reason and rigor: How conceptual frameworks guide

research. Los Angeles, CA: Sage Publications

Reid, K. (2002). Truancy: short and long-term solutions. New York, New York: Routledge

Falmer.

120

Reyes, A. (2020). Compulsory school attendance: The new American crime. Education

Sciences, 10(75). doi:10.3390/educsci10030075 www.mdpi.com/journal/education

Shah, S. (2017). The Importance of Socialization in Society. Sociology Discussion.

https://www.sociologydiscussion.com/socialization/the-importance-of-socialization-in-

society/2200

Theory, S. L. (2017). Social learning theory. Psychology Today. Retrieved from

https://www.psychologytoday.com/us/basics/social-learning-theory

Van Eck, K., Johnson, S. R., Bettencourt, A., & Johnson, S. L. (2017). How school climate

relates to chronic absenteeism: A multi-level latent profile analysis. Journal of School

Psychology, 61, 89-102.

Whitney, C. R., & Liu, J. (2017). What we’re missing: A descriptive analysis of part-day

absenteeism in secondary school. AERA Open, 3(2), 1-17

United State Department of Education. (2016a). Key data highlights on equity and opportunity

gaps in our nation's public schools. 2013-2014 civil rights data collection. A first look.

Revised. Office for Civil Rights, U.S. Department of Education.

United States Department of Education. (2016b, June 7). Chronic absenteeism in the nation’s

schools. Retrieved from https://www2.ed.gov/datastory/chronicabsenteeism.html

United States Department of Justice. (2015, October). Every student, every day: A community

toolkit to address and eliminate chronic absenteeism.

chronic absenteeism at one arkansas high school

Documents